Quantifying kinetic paths of protein folding

We propose a new approach to activated protein folding dynamics via a diffusive path integral framework. The important issues of kinetic paths in this situation can be directly addressed. This leads to the identification of the kinetic paths of the activated folding process, and provides a direct tool and language for the theoretical and experimental community to understand the problem better. The kinetic paths giving the dominant contributions to the long-time folding activation dynamics can be quantitatively determined. These are shown to be the instanton paths. The contributions of these instanton paths to the kinetics lead to the "bell-like" shape folding rate dependence on temperature, which is in good agreement with folding kinetic experiments and simulations. The connections to other approaches as well as the experiments of the protein folding kinetics are discussed.     

Optimal specificity and function for flexible biomolecular recognition

Biomolecular associations often accompanied by large conformational changes, sometimes folding and unfolding. By exploring an exactly solvable model, we constructed the free energy landscape and established a general framework for studying the biomolecular flexible binding process. We derived an optimal criterion for the specificity and function for flexible biomolecular binding where the binding and conformational folding are coupled.     

Structural aspects of biomolecular recognition and self-assembly

Proteins are capable of fulfilling two important features of any likely system of bioelectronics: the ability to recognise other molecules with exquisite specificity, and the ability to self-assemble, in vivo and in vitro, to generate an astonishing variety of three-dimensional structures. Much current work is aimed at the redesign of existing proteins, either as an end in itself or as a means of developing the knowledge-base necessary for the ab initio design of novel proteins. This type of study has been greatly facilitated by the discovery of the modular or domain structure of many proteins, leading to concepts of protein manipulation as a kind of molecular Lego.     

Quantifying the kinetic parameters of prion replication.

The mechanism of protein-only prion replication is controversial. A detailed mathematical model of prion replication by nucleated polymerisation is developed, and its parameters are estimated from published data. PrP-res decay is around two orders of magnitude slower than PrP-sen decay, a plausible ratio of two parameters estimated from very different experiments. By varying the polymer breakage rate, we reveal that systems of short polymers grow the fastest. Drugs which break polymers could therefore accelerate disease progression. Growth in PrP-res seems slower than growth in infectious titre. This can be explained either by a novel hypothesis concerning inoculum clearance from a newly infected brain, or by the faster growth of compartments containing smaller polymers. The existence of compartments can also explain why prion growth sometimes reaches a plateau. Published kinetic data are all compatible with our mathematical model, so the nucleated polymerisation hypothesis cannot be ruled out on dynamic grounds.     

Exploring biomolecular recognition using optical biosensors.

Understanding the basic forces that determine molecular recognition helps to elucidate mechanisms of biological processes and facilitates discovery of innovative biotechnological methods and materials for therapeutics, diagnostics, and separation science. The ability to measure interaction properties of biological macromolecules quantitatively across a wide range of affinity, size, and purity is a growing need of studies aimed at characterizing biomolecular interactions and the structural elements that drive them. Optical biosensors have provided an increasingly impactful technology for such biomolecular interaction analyses. These biosensors record the binding and dissociation of macromolecules in real time by transducing the accumulation of mass of an analyte molecule at the sensor surface coated with ligand molecule into an optical signal. Interactions of analytes and ligands can be analyzed at a microscale and without the need to label either interactant. Sensors enable the detection of bimolecular interaction as well as multimolecular assembly. Most notably, the method is quantitative and kinetic, enabling determination of both steady-state and dynamic parameters of interaction. This article describes the basic methodology of optical biosensors and presents several examples of its use to investigate such biomolecular systems as cytokine growth factor-receptor recognition, coagulation factor assembly, and virus-cell docking.     

Biophysical view of the role of interfaces in biomolecular recognition

Molecular recognition plays a key role in life. Macromolecular interactions at and with interfaces are of paramount importance in this respect. It is therefore crucial to understand and quantify the forces near the surfaces of biological interest in sufficient detail. Specific binding of large molecules, such as antibodies, is affected by the proximity of polar surfaces, for example. On the one hand, the presence of the net surface charges may raise or lower the local macromolecular concentration depending on the relative sign of the charges involved. On the other hand, the ligands attached to strongly polar surfaces always attract and bind their corresponding antibodies less efficiently than the corresponding dissolved molecules. The reason for this is the non-Coulombic repulsion between the ligand-presenting polar surface and the approaching macromolecule. This force is promoted by the surface hydrophilicity and the width of the interfacial region. A simple, direct hydration force is seldom, if ever, seen in such systems. (This is owing to the very short range (Lambda (h ) reverse similar 0.1 nm ) of pure hydration force.) The non-specific adsorption of proteins to the lipid bilayer is also little affected by the overall repulsion between the macromolecule and the bilayer surface; such an adsorption is governed more by the number of defects and/or by the availability of the hydrophobic binding sites in the interfacial region. Artificial lipid membranes typically offer numerous such binding sites to the surrounding macromolecules. Multiple non-specific protein adsorption, which results in partial macromolecular denaturation or complement activation, is therefore one of the main reasons for the rapid elimination of lipid vesicles from the blood stream in vivo. To promote the circulation time of an intravenously injected lipid suspension it is therefore necessary to modify the surfaces of their constituent lipid bilayers. Increasing the surface net charge density and/or increasing the bilayer surface hydrophilicity is of little use in this respect. In order to affect the non-specific bilayer-protein interactions significantly, an optimal number of water-soluble, short and sufficiently mobile polymers must be attached to the lipid head-groups. These polymers then increase the repulsive barrier of the membrane surface dramatically, due to the generation of a thick and mobile as well as strongly hydrated interface. Owing to this, the affinity for proteins of the resulting surface is lowered and the surface-induced protein denaturation or complement insertion is hampered. Polymer-coated liposomes, consequently, are not attractive for the phagocytic cells. Such liposomes, consequently, remain in the blood circulation much longer than simple lipid vesicles; the former, consequently, may spontaneously accumulate in tumors.     

Transport and kinetic processes underlying biomolecular interactions in the BIACORE optical biosensor

The transport and kinetic processes describing biomolecular interactions in the BIACORE optical biosensor have been studied with the help of a mathematical model. In comparison to previous models, the model presented here couples, for the first time, transport phenomena in the flow channel with hindered diffusive transport and reactions inside the hydrogel. Simulated experiments based on this model, and two simpler models extant in the literature, are used to identify cases under which the detailed model is essential for accurate prediction of kinetic parameters. It is shown that this model can substantially improve the accuracy of kinetic parameter estimation when transport limitations in the flow channel and/or the hydrogel significantly influence the observed instrument response curves. The model can extend the range of the instrument's applicability to higher concentrations of immobilized species within the hydrogel. It can also be used for accurate design of experiments with the purpose of minimizing errors in the estimation of the kinetic parameters.     

A biomolecular recognition approach for the functionalization of cellulose with gold nanoparticles

Materials with new and improved functionalities can be obtained by modifying cellulose with gold nanoparticles (AuNPs) via the in situ reduction of a gold precursor or the deposition or covalent immobilization of pre‐synthesized AuNPs. Here, we present an alternative biomolecular recognition approach to functionalize cellulose with biotin‐AuNPs that relies on a complex of 2 recognition elements: a ZZ‐CBM3 fusion that combines a carbohydrate‐binding module (CBM) with the ZZ fragment of the staphylococcal protein A and an anti‐biotin antibody. Paper and cellulose microparticles with AuNPs immobilized via the ZZ‐CBM3:anti‐biotin IgG supramolecular complex displayed an intense red color, whereas essentially no color was detected when AuNPs were deposited over the unmodified materials. Scanning electron microscopy analysis revealed a homogeneous distribution of AuNPs when immobilized via ZZ‐CBM3:anti‐biotin IgG complexes and aggregation of AuNPs when deposited over paper, suggesting that color differences are due to interparticle plasmon coupling effects. The approach could be used to functionalize paper substrates and cellulose nanocrystals with AuNPs. More important, however, is the fact that the occurrence of a biomolecular recognition event between the CBM‐immobilized antibody and its specific, AuNP‐conjugated antigen is signaled by red color. This opens up the way for the development of simple and straightforward paper/cellulose‐based tests where detection of a target analyte can be made by direct use of color signaling.     

Gene recognition based on DAG shortest paths

We describe DAGGER, an ab initio gene recognition program which combines the output of high dimensional signal sensors in an intuitive gene model based on directed acyclic graphs. In the first stage, candidate start, donor, acceptor, and stop sites are scored using the SNoW learning architecture. These sites are then used to generate a directed acyclic graph in which each source-sink path represents a possible gene structure. Training sequences are used to optimize an edge weighting function so that the shortest source-sink path maximizes exon-level prediction accuracy. Experimental evaluation of prediction accuracy on two benchmark data sets demonstrates that DAGGERis competitive with ab initio gene finding programs based on Hidden Markov Models.     

Quantifying the kinetic stability of hyperstable proteins via time-dependent SDS trapping

Globular proteins are usually in equilibrium with unfolded conformations, whereas kinetically stable proteins (KSPs) are conformationally trapped by their high unfolding transition state energy. Kinetic stability (KS) could allow proteins to maintain their activity under harsh conditions, increase a protein's half-life, or protect against misfolding-aggregation. Here we show the development of a simple method for quantifying a protein's KS that involves incubating a protein in SDS at high temperature as a function of time, running the unheated samples on SDS-PAGE, and quantifying the bands to determine the time-dependent loss of a protein's SDS resistance. Six diverse proteins, including two monomer, two dimers, and two tetramers, were studied by this method, and the kinetics of the loss of SDS resistance correlated linearly with their unfolding rate determined by circular dichroism. These results imply that the mechanism by which SDS denatures proteins involves conformational trapping, with a trapping rate that is determined and limited by the rate of protein unfolding. We applied the SDS trapping of proteins (S-TraP) method to superoxide dismutase (SOD) and transthyretin (TTR), which are highly KSPs with native unfolding rates that are difficult to measure by conventional spectroscopic methods. A combination of S-TraP experiments between 75 and 90 °C combined with Eyring plot analysis yielded an unfolding half-life of 70 ± 37 and 18 ± 6 days at 37 °C for SOD and TTR, respectively. The S-TraP method shown here is extremely accessible, sample-efficient, cost-effective, compatible with impure or complex samples, and will be useful for exploring the biological and pathological roles of kinetic stability.     

Ultrafast dynamics-driven biomolecular recognition where fast activities dictate slow events

In general, biological macromolecules require significant dynamical freedom to carry out their different functions, including signal transduction, metabolism, catalysis and gene regulation. Effectors (ligands, DNA and external milieu, etc) are considered to function in a purely dynamical manner by selectively stabilizing a specific dynamical state, thereby regulating biological function. In particular, proteins in presence of these effectors can exist in several dynamical states with distinct binding or enzymatic activity. Here, we have reviewed the efficacy of ultrafast fluorescence spectroscopy to monitor the dynamical flexibility of various proteins in presence of different effectors leading to their biological activity. Recent studies demonstrate the potency of a combined approach involving picosecond-resolved Förster resonance energy transfer, polarisation-gated fluorescence and time-dependent stokes shift for the exploration of ultrafast dynamics in biomolecular recognition of various protein molecules. The allosteric protein–protein recognition following differential protein–DNA interaction is shown to be a consequence of some ultrafast segmental motions at the C-terminal of Gal repressor protein dimer with DNA operator sequences O_E and O_I. Differential ultrafast dynamics at the C-terminal of λ-repressor protein with two different operator DNA sequences for the protein–protein interaction with different strengths is also reviewed. We have also systemically briefed the study on the role of ultrafast dynamics of water molecules on the functionality of enzyme proteins α-chymotrypsin and deoxyribonuclease I. The studies on the essential ultrafast dynamics at the active site of the enzyme α-chymotrypsin by using an anthraniloyl fluorescent extrinsic probe covalently attached to the serine-195 residue for the enzymatic activity at homeothermic condition has also been reviewed. Finally, we have highlighted the evidence that a photoinduced dynamical event dictates the molecular recognition of a photochromic ligand, dihydroindolizine with the serine protease α-chymotrypsin and with a liposome (L-α-phosphatidylcholine).     

Amino acids-nucleotides biomolecular recognition: from biological occurrence to affinity chromatography

In this review, the protein-DNA interactions are discussed considering different perspectives, and the biological occurrence of this interaction is explained at atomic level. The evaluation of the amino acid-nucleotide recognition has been investigated analysing datasets for predicting the association preferences and the geometry that favours the interaction. Based on this knowledge, an affinity chromatographic method was developed also exploiting this biological favoured contact. In fact, the implementation of this technique brings the possibility to apply the concept of molecular interactions to the development of new purification methodologies. In addition, the integration of the information recovered by all the different perspectives can bring new insights about some biological mechanisms, though not totally clarified.     

Divergent paths,the pursuit of cultural recognition in Aotearoa New Zealand

Stimulated by a recent government ban on kosher slaughter (shechita), and a whale stranding involving Ngāti Toa near Wellington, the author compares the quests of Indigenous and minority groups for cultural rights in Aotearoa (New Zealand). Observing Māori and Jews navigating in the contexts of the Treaty of Waitangi and human rights legislation, this paper provides concrete ethnographic examples that highlight how such claims articulate with the political and legal contexts in this Antipodean nation.     

A method for biomolecular structural recognition and docking allowing conformational flexibility.

In this work, we present an algorithm developed to handle biomolecular structural recognition problems, as part of an interdisciplinary research endeavor of the Computer Vision and Molecular Biology fields. A key problem in rational drug design and in biomolecular structural recognition is the generation of binding modes between two molecules, also known as molecular docking. Geometrical fitness is a necessary condition for molecular interaction. Hence, docking a ligand (e.g., a drug molecule or a protein molecule), to a protein receptor (e.g., enzyme), involves recognition of molecular surfaces. Conformational transitions by "hinge-bending" involves rotational movements of relatively rigid parts with respect to each other. The generation of docked binding modes between two associating molecules depends on their three dimensional structures (3-D) and their conformational flexibility. In comparison to the particular case of rigid-body docking, the computational difficulty grows considerably when taking into account the additional degrees of freedom intrinsic to the flexible molecular docking problem. Previous docking techniques have enabled hinge movements only within small ligands. Partial flexibility in the receptor molecule is enabled by a few techniques. Hinge-bending motions of protein receptors domains are not addressed by these methods, although these types of transitions are significant, e.g., in enzymes activity. Our approach allows hinge induced motions to exist in either the receptor or the ligand molecules of diverse sizes. We allow domains/subdomains/group of atoms movements in either of the associating molecules. We achieve this by adapting a technique developed in Computer Vision and Robotics for the efficient recognition of partially occluded articulated objects. These types of objects consist of rigid parts which are connected by rotary joints (hinges). Our method is based on an extension and generalization of the Hough transform and the Geometric Hashing paradigms for rigid object recognition. We show experimental results obtained by the successful application of the algorithm to cases of bound and unbound molecular complexes, yielding fast matching times. While the "correct" molecular conformations of the known complexes are obtained with small RMS distances, additional, predictive good-fitting binding modes are generated as well. We conclude by discussing the algorithm's implications and extensions, as well as its application to investigations of protein structures in Molecular Biology and recognition problems in Computer Vision.     

A kinetic recognition process for tRNA at the ribosome

In order to explain the great accuracy when amino acids are selected in protein synthesis, some authors have proposed a kinetic recognition process driven out of thermodynamic equilibrium. In this work, such a process for the recognition of the tRNA anticodon at the ribosome is considered. An important feature is that the discrimination possibility is determined not only by the differences of codon-anticodon binding energy (the only specific quantity) but also by the total binding energy including non specific bonds of other tRNA groups to the ribosome. In the context of this, the effects of streptomycin, and related features of mutant ribosome proteins or tRNA's which decrease or increase the selection accuracy can be interpreted by the kinetic model.     

Detection and characterization of weak affinity antibody antigen recognition with biomolecular interaction analysis

In biological systems, weak-affinity interactions (association constant, K_a, of less than approximately 10⁴ M ⁻¹) between biomolecules are common and essential to the integrity of such units. However, studies of weak biological interactions are difficult due to the scarcity of analytical methods available for the bioscientist. In this communication, we report on the use of biosensors based on surface plasmon resonance to detect and characterize weak affinity antibody–antigen interactions. Monoclonal antibodies towards carbohydrate antigens were immobilized on sensor surfaces and were used to detect weak binding of the carbohydrate tetraglucose of dissociation constant, K_d, in the millimolar range. Sensorgrams were received in the form of square pulses where the kinetic rate constants were difficult to assess due to the rapid association and dissociation of the antigen to/from the immobilized antibody. © 1997 John Wiley & Sons, Ltd.     

A multidomain flexible docking approach to deal with large conformational changes in the modeling of biomolecular complexes

Binding-induced backbone and large-scale conformational changes represent one of the major challenges in the modeling of biomolecular complexes by docking. To address this challenge, we have developed a flexible multidomain docking protocol that follows a "divide-and-conquer" approach to model both large-scale domain motions and small- to medium-scale interfacial rearrangements: the flexible binding partner is treated as an assembly of subparts/domains that are docked simultaneously making use of HADDOCK's multidomain docking ability. For this, the flexible molecules are cut at hinge regions predicted using an elastic network model. The performance of this approach is demonstrated on a benchmark covering an unprecedented range of conformational changes of 1.5 to 19.5 ?. We show from a statistical survey of known complexes that the cumulative sum of eigenvalues obtained from the elastic network has some predictive power to indicate the extent of the conformational change to be expected.     

Understanding biomolecular motion,recognition, and allostery by use of conformational ensembles

We review the role conformational ensembles can play in the analysis of biomolecular dynamics, molecular recognition, and allostery. We introduce currently available methods for generating ensembles of biomolecules and illustrate their application with relevant examples from the literature. We show how, for binding, conformational ensembles provide a way of distinguishing the competing models of induced fit and conformational selection. For allostery we review the classic models and show how conformational ensembles can play a role in unravelling the intricate pathways of communication that enable allostery to occur. Finally, we discuss the limitations of conformational ensembles and highlight some potential applications for the future.