Biomolecular Recognition Processes Research Articles

Resolving Protein Conformational Plasticity and Substrate Binding via Machine Learning.

A long-standing target in elucidating the biomolecular recognition process is the identification of binding-competent conformations of the receptor protein. However, protein conformational plasticity and the stochastic nature of the recognition processes often preclude the assignment of a specific protein conformation to an individual ligand-bound pose. Here, we demonstrate that a computational framework coined as RF-TICA-MD, which integrates an ensemble decision-tree-based Random Forest (RF) machine learning (ML) technique with an unsupervised dimension reduction approach time-structured independent component analysis (TICA), provides an efficient and unambiguous solution toward resolving protein conformational plasticity and the substrate binding process. In particular, we consider multimicrosecond-long molecular dynamics (MD) simulation trajectories of a ligand recognition process in solvent-inaccessible cavities of archetypal proteins T4 lysozyme and cytochrome P450cam. We show that in a scenario in which clear correspondence between protein conformation and binding-competent macrostates could not be obtained via an unsupervised dimension reduction approach, an a priori decision-tree-based supervised classification of the simulated recognition trajectories via RF would help characterize key amino acid residue pairs of the protein that are deemed sensitive for ligand binding. A subsequent unsupervised dimensional reduction of the selected residue pairs via TICA would then delineate a conformational landscape of protein which is able to demarcate ligand-bound poses from unbound ones. The proposed RF-TICA-MD approach is shown to be data agnostic and found to be robust when using other ML-based classification methods such as XGBoost. As a promising spinoff of the protocol, the framework is found to be capable of identifying distal protein locations which would be allosterically important for ligand binding and would characterize their roles in recognition pathways. A Python implementation of a proposed ML workflow is available in GitHub https://github.com/navjeet0211/rf-tica-md.

Impact of Inert Crowders on Host-Guest Recognition Process.

Biological environments typically contain high concentrations (300-400 mg/mL) of different macromolecules at volume fractions as large as 30%-40%. Biomolecular recognition processes, a ubiquitous biological phenomena, occurring in such crowded heterogeneous media would differ significantly compared to the dilute buffer solutions. Here we quantify the potential impact of inert crowders on prototypical host-guest recognition process by explicit-solvent molecular dynamics (MD) simulations in atomic resolution. We demonstrate that the crowders, when smaller in size, would facilitate the binding process of the guest molecule by decreasing the free energy barrier for binding via excluded volume effect and desolvation of the host receptor. However, the extent of crowder-induced stabilization of a host-guest complex is found to be significantly higher when the guest molecule is sterically constricted to approach the host along a centrosymmetric direction, compared to its unrestricted, freely diffusive movement. A kinetic analysis of the recognition process reveals that the origin of a relatively stronger crowder impact during constricted movement of guest molecule lies in the relatively enhanced residence time of the guest inside the host by crowders. Together, our results suggest that the extent of impact of crowding on recognition processes would be contingent upon the presence or absence of constriction on ligand movement.

Construction of a photoelectrochemical immunosensor based on CuInS2 photocathode and BiVO4/BiOI/Ag2S photoanode and sensitive detection of NSE

In this paper, a photoelectrochemical (PEC) immunosensor was constructed to detect neuron-specific enolase (NSE) with ITO/BiVO4/BiOI/Ag2S as photoanode and ITO/CuInS2 as photocathode. Due to its excellent photocurrent response, Ag2S sensitized BiVO4/BiOI composite was selected to provide stable photocurrent in place of the traditional Pt electrode. ITO/CuInS2 electrode was used to immobilize biomolecules, which solved the deficiency of poor anti-interference ability of single photoanode. Under the optimal experimental conditions, the PEC immunosensor had outstanding linear relationship within the range of NSE concentration from 5 pg/mL-200 ng/mL, and the detection limit was 1.2 pg/mL. The constructed PEC immunosensor had two advantages. On the one hand, the PEC immunosensor was built on the photocathode, which had better anti-interference ability because of the separation of light capture and biomolecular recognition process. On the other hand, the introduction of photoanode increased the photocurrent response and reduced the detection limit of target antigen. The PEC immunosensor had good stability, reproducibility and specificity, and provided a broad prospect for the detection of other molecules.

Current Advances in Aptamer-based Biomolecular Recognition and Biological Process Regulation.

The interaction between biomolecules with their target ligands plays a great role in regulating biological functions. Aptamers are short oligonucleotide sequences that can specifically recognize target biomolecules via structural complementarity and thus regulate related biological functions. In the past ten years, aptamers have made great progress in target biomolecule recognition, becoming a powerful tool to regulate biological functions. At present, there are many reviews on aptamers applied in biomolecular recognition, but few reviews pay attention to aptamer-based regulation of biological functions. Here, we summarize the approaches to enhancing aptamer affinity and the advancements of aptamers in regulating enzymatic activity, cellular immunity and cellular behaviors. Furthermore, this review discusses the challenges and future perspectives of aptamers in target recognition and biological functions regulation, aiming to provide some promising ideas for future regulation of biomolecular functions in a complex biological environment.

Solvent's Role in Cavity-Ligand Recognition Would Depend on the Mode of Ligand Diffusion.

Solvent is known to play crucial roles in dictating the thermodynamics and kinetics of the biomolecular recognition process. Here, we show that the extent of significance of water in modulating the ligand recognition process is critically contingent on the ligand diffusion and on the constraints introduced on it. Toward the end, we use a well-known prototypical system of spherical ligand diffusing freely toward a hydrophobic concave cavity in explicit water. We analyze a large series of adaptively sampled unbiased molecular dynamics simulation trajectories within the framework of time-structured independent component analysis (TICA). Our quantitative investigations reveal that water would play a significant role in the ligand recognition process, provided that the ligand is constricted to diffuse along a centro-symmetric fashion. On the contrary, water's contribution in the ligand recognition process would diminish to a negligible value if the ligand freely diffuses toward the pocket. A Markov state model (MSM) constructed using the simulated trajectories identifies a set of transiently populated metastable states comprising partially ligand-unbound macro states, alongside ligand-bound and ligand-unbound pose and gives rise to multiple transition paths of ligand in its way to the hydrophobic cavity. Lifting the restriction on ligand movement changes its binding pathway, time scales, and the extent of the role of solvent in modulating the recognition process.

Spectrally Resolved Estimation of Water Entropy in the Active Site of Human Carbonic Anhydrase II.

A major challenge in understanding ligand binding to biomacromolecules lies in dissecting the underlying thermodynamic driving forces at the atomic level. Quantifying the contributions of water molecules is often especially demanding, although they can play important roles in biomolecular recognition and binding processes. One example is human carbonic anhydrase II, whose active site harbors a conserved network of structural water molecules that are essential for enzymatic catalysis. Inhibitor binding disrupts this water network and changes the hydrogen-bonding patterns in the active site. Here, we use atomistic molecular dynamics simulations to compute the absolute entropy of the individual water molecules confined in the active site of hCAII using a spectrally resolved estimation (SRE) approach. The entropy decrease of water molecules that remain in the active site upon binding of a dorzolamide inhibitor is caused by changes in hydrogen bonding and stiffening of the hydrogen-bonding network. Overall, this entropy decrease is overcompensated by the gain due to the release of three water molecules from the active site upon inhibitor binding. The spectral density calculations enable the assignment of the changes to certain vibrational modes. In addition, the range of applicability of the SRE approximation is systematically explored by exploiting the gradually changing degree of immobilization of water molecules as a function of the distance to a phospholipid bilayer surface, which defines an "entropy ruler". These results demonstrate the applicability of SRE to biomolecular solvation, and we expect it to become a useful method for entropy calculations in biomolecular systems.

An Appraisal of Computer Simulation Approaches in Elucidating Biomolecular Recognition Pathways.

Computer simulation approaches in biomolecular recognition processes have come a long way. In this Perspective, we highlight a series of recent success stories in which computer simulations have played a remarkable role in elucidating the atomic resolution mechanism of kinetic processes of protein-ligand binding in a quantitative fashion. In particular, we show that a robust combination of unbiased simulation, harnessed by a high-fidelity computing environment, and Markov state modeling approaches has been instrumental in revealing novel protein-ligand recognition pathways in multiple systems. We also elucidate the role of recent developments in enhanced sampling approaches in providing the much-needed impetus in accelerating simulation of the ligand recognition process. We identify multiple key issues, including force fields and the sampling bottleneck, which are currently preventing the field from achieving quantitative reconstruction of experimental measurements. Finally, we suggest a possible way forward via adoption of multiscale approaches and coarse-grained simulations as next steps toward efficient elucidation of ligand binding kinetics.

Enhanced peroxidase-like activity of boron nitride quantum dots anchored porous CeO2 nanorods by aptamer for highly sensitive colorimetric detection of kanamycin

Kanamycin (KAN) residue in the environment and food have a huge risk to human health, therefore, designing simple and sensitive determination methods for KAN is in high demand. Here, a simple and low-cost colorimetric analysis was established for highly sensitive determination of KAN through integrating boron nitride quantum dots anchored porous CeO2 nanorods (BNQDs/CeO2) and aptamer. The BNQDs/CeO2 as nanozyme showed prominent peroxidase-like activity, which could effectively catalyze 3,3′,5,5′-tetramethylbenzidine (TMB) oxidation by H2O2 because of large surface area and synergetic interaction between BNQDs and CeO2. Moreover, it presented an obviously enhanced catalytic activity after combing with KAN-specific aptamer, resulting from the increased dispersibility and substrate affinity of BNQDs/CeO2 nanozyme. While KAN could restrain such a catalytic enhancement through aptamer-target recognition event. On the basis of aptamer-regulated mimic enzyme activity, the proposed colorimetric method realized quantitative KAN determination ranging from 0.01 nM to 100 nM with an ultralow detection limit of 4.6 pM. This analysis method is facile in design and can be applied to other biomolecular recognition processes, promising as a universal detection platform for environmental monitoring and food safety.

Phosphoprotein Detection with a Single Nanofluidic Diode Decorated with Zinc Chelates.

We report a nanofluidic device for the label-free detection of phosphoprotein (PPn) analytes. To achieve this goal, a metal ion chelator, namely 4-[bis(2-pyridylmethyl)aminomethyl]aniline (DPA-NH2 ) compound was synthesized. Single asymmetric nanofluidic channels were fabricated in polyethylene terephthalate (PET) membranes. The chelator (DPA-NH2 ) molecules are subsequently immobilized on the nanochannel surface, followed by the zinc ion complexation to afford DPA-Zn2+ chelates, which act as ligand moieties for the specific binding of phosphoproteins. The success of the chemical reaction and biomolecular recognition process that occur in a confined geometry can be monitored from the changes in electrical readout of the nanochannel. The nanofluidic sensor has the ability to sensitively and specifically detect lower concentrations (≥1 nM) of phosphoprotein (albumin and α-casein) in the surrounding environment as evidenced from the significant decrease in ion current flowing through the nanochannels. However, dephosphoproteins such as lysozyme and dephospho-α-casein even at higher concentration (>1 μM) could not induce any significant change in the transmembrane ion flux. This observation indicated the sensitivity and specificity of the proposed nanofluidic sensor towards PPn proteins, and has potential for use in differentiating between phosphoproteins and dephosphoproteins.

Investigation into Early Steps of Actin Recognition by the Intrinsically Disordered N-WASP Domain V.

Cellular regulation or signaling processes are mediated by many proteins which often have one or several intrinsically disordered regions (IDRs). These IDRs generally serve as binders to different proteins with high specificity. In many cases, IDRs undergo a disorder-to-order transition upon binding, following a mechanism between two possible pathways, the induced fit or the conformational selection. Since these mechanisms contribute differently to the kinetics of IDR associations, it is important to investigate them in order to gain insight into the physical factors that determine the biomolecular recognition process. The verprolin homology domain (V) of the Neural Wiskott–Aldrich Syndrome Protein (N-WASP), involved in the regulation of actin polymerization, is a typical example of IDR. It is composed of two WH2 motifs, each being able to bind one actin molecule. In this study, we investigated the early steps of the recognition process of actin by the WH2 motifs of N-WASP domain V. Using docking calculations and molecular dynamics simulations, our study shows that actin is first recognized by the N-WASP domain V regions which have the highest propensity to form transient -helices. The WH2 motif consensus sequences “LKKV” subsequently bind to actin through large conformational changes of the disordered domain V.

Interaction of copper (II) complexes by bovine serum albumin: spectroscopic and calorimetric insights

Serum albumins being the most abundant proteins in the blood and cerebrospinal fluid are significant carriers of essential transition metal ions in the human body. Studies of copper (II) complexes have gained attention because of their potential applications in synthetic, biological, and industrial processes. Study of binding interactions of such bioinorganic complexes with serum albumins improves our understanding of biomolecular recognition process essential for rational drug design. In the present investigation, we have applied quantitative approach to explore interactions of novel synthesized copper (II) complexes viz. [Cu(L1)(L2)ClO4] (complex I), [Cu(L2)(L3)]ClO4] (complex II) and [Cu(L4)2(H2O)2] (complex III) with bovine serum albumin (BSA) to evaluate their binding characteristics, site and mode of interaction. The fluorescence quenching of BSA initiated by complexation has been observed to be static in nature. The binding interactions are endothermic driven by entropic factors as confirmed by high sensitivity isothermal titration calorimetry. Changes in secondary and tertiary structure of protein have been studied by circular dichroism and significant reduction in α-helical content of BSA was observed upon binding. Site marking experiments with warfarin and ibuprofen indicated that copper complexes bind at site II of the protein.

Dynamics Govern Specificity of a Protein-Protein Interface: Substrate Recognition by Thrombin.

Biomolecular recognition is crucial in cellular signal transduction. Signaling is mediated through molecular interactions at protein-protein interfaces. Still, specificity and promiscuity of protein-protein interfaces cannot be explained using simplistic static binding models. Our study rationalizes specificity of the prototypic protein-protein interface between thrombin and its peptide substrates relying solely on binding site dynamics derived from molecular dynamics simulations. We find conformational selection and thus dynamic contributions to be a key player in biomolecular recognition. Arising entropic contributions complement chemical intuition primarily reflecting enthalpic interaction patterns. The paradigm “dynamics govern specificity” might provide direct guidance for the identification of specific anchor points in biomolecular recognition processes and structure-based drug design.

Free energetics of rigid body association of ubiquitin binding domains: A biochemical model for binding mediated by hydrophobic interaction

Weak intermolecular interactions, such as hydrophobic associations, underlie numerous biomolecular recognition processes. Ubiquitin is a small protein that represents a biochemical model for exploring thermodynamic signatures of hydrophobic association as it is widely held that a major component of ubiquitin's binding to numerous partners is mediated by hydrophobic regions on both partners. Here, we use atomistic molecular dynamics simulations in conjunction with the Adaptive Biasing Force sampling method to compute potentials of mean force (the reversible work, or free energy, associated with the binding process) to investigate the thermodynamic signature of complexation in this well-studied biochemical model of hydrophobic association. We observe that much like in the case of a purely hydrophobic solute (i.e., graphene, carbon nanotubes), association is favored by entropic contributions from release of water from the interprotein regions. Moreover, association is disfavored by loss of enthalpic interactions, but unlike in the case of purely hydrophobic solutes, in this case protein-water interactions are lost and not compensated for by additional water-water interactions generated upon release of interprotein and moreso, hydration, water. We further find that relative orientations of the proteins that mutually present hydrophobic regions of each protein to its partner are favored over those that do not. In fact, the free energy minimum as predicted by a force field based method recapitulates the experimental NMR solution structure of the complex.

Heterogeneous Hydration of p53/MDM2 Complex.

Water-mediated interactions play critical roles in biomolecular recognition processes. Explicit solvent molecular dynamics (MD) simulations and the variational implicit-solvent model (VISM) are used to study those hydration properties during binding for the biologically important p53/MDM2 complex. Unlike simple model solutes, in such a realistic and heterogeneous solute–solvent system with both geometrical and chemical complexity, the local water distribution sensitively depends on nearby amino acid properties and the geometric shape of the protein. We show that the VISM can accurately describe the locations of high and low density solvation shells identified by the MD simulations and can explain them by a local coupling balance of solvent–solute interaction potentials and curvature. In particular, capillary transitions between local dry and wet hydration states in the binding pocket are captured for interdomain distance between 4 to 6 Å, right at the onset of binding. The underlying physical connection between geometry and polarity is illustrated and quantified. Our study offers a microscopic and physical insight into the heterogeneous hydration behavior of the biologically highly relevant p53/MDM2 system and demonstrates the fundamental importance of hydrophobic effects for biological binding processes. We hope our study can help to establish new design rules for drugs and medical substances.

Adaptive Biasing Combined with Hamiltonian Replica Exchange to Improve Umbrella Sampling Free Energy Simulations.

The accurate calculation of potentials of mean force for ligand-receptor binding is one of the most important applications of molecular simulation techniques. Typically, the separation distance between ligand and receptor is chosen as a reaction coordinate along which a PMF can be calculated with the aid of umbrella sampling (US) techniques. In addition, restraints can be applied on the relative position and orientation of the partner molecules to reduce accessible phase space. An approach combining such phase space reduction with flattening of the free energy landscape and configurational exchanges has been developed, which significantly improves the convergence of PMF calculations in comparison with standard umbrella sampling. The free energy surface along the reaction coordinate is smoothened by iteratively adapting biasing potentials corresponding to previously calculated PMFs. Configurations are allowed to exchange between the umbrella simulation windows via the Hamiltonian replica exchange method. The application to a DNA molecule in complex with a minor groove binding ligand indicates significantly improved convergence and complete reversibility of the sampling along the pathway. The calculated binding free energy is in excellent agreement with experimental results. In contrast, the application of standard US resulted in large differences between PMFs calculated for association and dissociation pathways. The approach could be a useful alternative to standard US for computational studies on biomolecular recognition processes.

Giant hollow MnL2n spherical complexes: structure, functionalisation and applications

Drawing inspiration from the self-assembly of hollow spherical virus capsids and protein cages found in nature, a family of roughly spherical coordination polyhedra with general formula MnL2n was designed and several members of the series have been synthesised. These spherical complexes are self-assembled upon reaction of bent bis(pyridine) ligands with Pd(2+) ions. The introduction of functional side chains into the ligands is straightforward, making the synthesis of both exo- and endohedrally functionalised spherical complexes possible. Accumulation of a high density of functional groups at the periphery of the spherical framework results in an enhancement of the weak interactions used in biomolecular recognition processes and the strong and selective interaction of the complex with a variety of substrates. Discrete and well-defined environments are generated within the spherical framework by functionalisation of the interior of the complex. These environments can be used for the selective encapsulation of guest molecules, including species as diverse as simple metal ions, fluoroalkanes and fullerenes. The well-defined cavity of the spherical complexes can also be exploited for the synthesis of precisely size-controlled nanoparticles and polymers. Most recently, a protein was successfully enclosed within a hollow self-assembled spherical complex, with a long-term view towards the control of protein functions for the development of new applications.

Glycopolymers and Glyco‐nanoparticles in Biomolecular Recognition Processes and Vaccine Development

With advances in polymerization techniques as well as selective chemical modification of carbohydrates, glycopolymers and glyco-nanoparticles are emerging as an important class of materials with tailored properties or novel nanotechnology-based platforms for a number of applications. The field of the so-called glyco-nanotechnology is starting to show some promises for future clinical applications. Glyco-nanoparticles, due to their versatile nature, could offer a platform for the design of carbohydrate-based vaccines and possibly allow the development of new single-dose vaccines in disease areas of unmet need. This paper surveys the emerging roles of carbohydrate-based polymeric and nanomaterials for biomolecular recognition processes and vaccine development.

A hydrogel-based versatile screening platform for specific biomolecular recognition in a well plate format

Precise determination of biomolecular interactions in high throughput crucially depends on a surface coating technique that allows immobilization of a variety of interaction partners in a non-interacting environment. We present a one-step hydrogel coating system based on isocyanate functional six-arm poly(ethylene oxide)-based star polymers for commercially available 96-well microtiter plates that combines a straightforward and robust coating application with versatile bio-functionalization. This system generates resistance to unspecific protein adsorption and cell adhesion, as demonstrated with fluorescently labeled bovine serum albumin and primary human dermal fibroblasts (HDF), and high specificity for the assessment of biomolecular recognition processes when ligands are immobilized on this surface. One particular advantage is the wide range of biomolecules that can be immobilized and convert the per se inert coating into a specifically interacting surface. We here demonstrate the immobilization and quantification of a broad range of biochemically important ligands, such as peptide sequences GRGDS and GRGDSK-biotin, the broadly applicable coupler molecule biocytin, the protein fibronectin, and the carbohydrates N-acetylglucosamine and N-acetyllactosamine. A simplified protocol for an enzyme-linked immunosorbent assay was established for the detection and quantification of ligands on the coating surface. Cell adhesion on the peptide and protein-modified surfaces was assessed using HDF. All coatings were applied using a one-step preparation technique, including bioactivation, which makes the system suitable for high-throughput screening in a format that is compatible with the most routinely used testing systems.

ChemInform Abstract: A Role for Ring‐Closing Metathesis in Medicinal Chemistry: Mimicking Secondary Architectures in Bioactive Peptides

AbstractReview: 141 refs.

Entropy Balance in the Intercalation Process of an Anti-Cancer Drug Daunomycin

The interplay of entropy components in a molecular recognition process is complex but intriguing. In this study, we probed into the origin of this interplay among the drug, DNA, and water entropy in the intercalation process (free → minor groove-bound → intercalation) of an anticancer drug daunomycin, resulting in small entropy difference (+1.1 kcal/mol) in excellent agreement with experiment (−1.1 kcal/mol). Using extensive all-atom simulations (>0.6 μs in total), followed by quasi- harmonic entropy calculation (with prior permutation reduction for water) and rigorous anharmonic and mutual information corrections, this study captures differing trends of drug and DNA entropy in different bound states. Overall water entropy change is positive although somewhat controlled due to the formation of bigger solvation layer in the bound states. This study encompasses for the first time all of the different entropy contributions including water in a biomolecular recognition process depicting entropy compensation similar to the ubiquitous enthalpy/entropy compensation prevalent in chemistry.