Role of fluctuations in ligand binding cooperativity of membrane receptors

Entropy driven cooperativity effect in multi-site drug optimization targeting SARS-CoV-2 papain-like protease

Papain-like protease (PLpro), a non-structural protein encoded by SARS-CoV-2, is an important therapeutic target. Regions 1 and 5 of an existing drug, GRL0617, can be optimized to produce cooperativity with PLpro binding, resulting in stronger binding affinity. This work investigated the origin of the cooperativity using molecular dynamics simulations combined with the interaction entropy (IE) method. The regions' improvement exhibits cooperativity by calculating the binding free energies between the complex of PLpro-inhibitor. The thermodynamic integration method further verified the cooperativity generated in the drug improvement. To further determine the specific source of cooperativity, enthalpy and entropy in the complexes were calculated using molecular mechanics/generalized Born surface area and IE. The results show that the entropic change is an important contributor to the cooperativity. Our study also identified residues P248, Q269, and T301 that play a significant role in cooperativity. The optimization of the inhibitor stabilizes these residues and minimizes the entropic loss, and the cooperativity observed in the binding free energy can be attributed to the change in the entropic contribution of these residues. Based on our research, the application of cooperativity can facilitate drug optimization, and provide theoretical ideas for drug development that leverage cooperativity by reducing the contribution of entropy through multi-locus binding.

Membrane-Mimetic Dendrimersomes Engulf Living Bacteria via Endocytosis

There is much interest in developing vesicular microcompartments from natural and synthetic amphiphiles, enabling programmable interactions with living matter. Of particular interest is the development of vesicles capable of endocytosis of living bacteria. Despite the complexity of this process, theoretical studies predict that the endocytosis of prolate micro-objects is possible without the need of active cell machinery if the energy released upon bacterial adhesion to the membrane surpasses the energy required to bend the membrane. Nonetheless, natural liposomes and synthetic polymersomes fail to sufficiently recapitulate membrane properties to perform this advanced function. Here we report the engulfment of living bacteria into endosomes by cell-like dendrimersomes assembled from Janus dendrimers. Full engulfment occurred in less than a minute after contact. The process is driven by the adhesion of the bacterium to the dendrimersome's membrane by ultraweak interactions, comparable to those utilized by nature. The key to success relies on the combination of high flexibility and stability of the dendrimersomes. The key properties of the dendrimersomes are programmed into the molecular structures of their building blocks. The ability to support endocytosis highlights opportunities for the design and programming of dendrimersomes in biomedical research.

Allostery in Its Many Disguises: From Theory to Applications

Allosteric regulation plays an important role in many biological processes, such as signal transduction, transcriptional regulation, and metabolism. Allostery is rooted in the fundamental physical properties of macromolecular systems, but its underlying mechanisms are still poorly understood. A collection of contributions to a recent interdisciplinary CECAM (Center Européen de Calcul Atomique et Moléculaire) workshop is used here to provide an overview of the progress and remaining limitations in the understanding of the mechanistic foundations of allostery gained from computational and experimental analyses of real protein systems and model systems. The main conceptual frameworks instrumental in driving the field are discussed. We illustrate the role of these frameworks in illuminating molecular mechanisms and explaining cellular processes, and describe some of their promising practical applications in engineering molecular sensors and informing drug design efforts.

Singular value decomposition for the correlation of atomic fluctuations with arbitrary angle

Many proteins exhibit a critical property called allostery, which enables intra-molecular transmission of information between distal sites. Microscopically, allosteric response is closely related to correlated atomic fluctuations. Conventional correlation analysis correlates the atomic fluctuations at two sites by taking the dot product (DP) between the fluctuations, which accounts only for the parallel and antiparallel components. Here, we present a singular value decomposition (SVD) method that analyzes the correlation coefficient of fluctuation dynamics with an arbitrary angle between the correlated directions. In a model allosteric system, the second PDZ domain (PDZ2) in the human PTP1E protein, approximately one third of the strong correlations have near-perpendicular directions, which are underestimated in the conventional method. The discrimination becomes more prominent for residue pairs with larger separation. The results of the proposed SVD method are more consistent with the experimentally determined PDZ2 dynamics than those of conventional method. In addition, the SVD method improved the prediction accuracy of the allosteric sites in a dataset of 23 known allosteric monomer proteins. The proposed method may inspire extended investigation not only into allostery, but also into protein dynamics and drug design.

Quasielastic neutron scattering in biology: Theory and applications

Neutrons scatter quasielastically from stochastic, diffusive processes, such as overdamped vibrations, localized diffusion and transitions between energy minima. In biological systems, such as proteins and membranes, these relaxation processes are of considerable physical interest. We review here recent methodological advances and applications of quasielastic neutron scattering (QENS) in biology, concentrating on the role of molecular dynamics simulation in generating data with which neutron profiles can be unambiguously interpreted. We examine the use of massively-parallel computers in calculating scattering functions, and the application of Markov state modeling. The decomposition of MD-derived neutron dynamic susceptibilities is described, and the use of this in combination with NMR spectroscopy. We discuss dynamics at very long times, including approximations to the infinite time mean-square displacement and nonequilibrium aspects of single-protein dynamics. Finally, we examine how neutron scattering and MD can be combined to provide information on lipid nanodomains. This article is part of a Special Issue entitled "Science for Life" Guest Editor: Dr. Austen Angell, Dr. Salvatore Magazù and Dr. Federica Migliardo.

A neutron spectrometer concept implementing RENS for studies in life sciences

BACKGROUND

Resolution Elastic Neutron Scattering (RENS) method involves performing elastic scattering intensity scans as a function of the instrumental energy resolution and as a function of temperature.

METHODS

In the framework of RENS, numerical simulation and experimental data show that in the measured elastic scattering law against the logarithm of the instrumental energy resolution an inflection point occurs when the resolution time intersects the system relaxation time; conversely, in the measured elastic scattering law against temperature an inflection point turns up when the system relaxation time intersects the resolution time.

RESULTS

For practical implementation of the RENS technique, a dedicated neutron spectrometer would be needed. Here we propose a concept of such a spectrometer that utilizes mechanical velocity selection of both incident and scattered neutrons over a wide angular range. The instrument is able to collect intensity scans vs energy resolution where the instrumental resolution time changes crisscrossing the system relaxation time, and intensity scans vs temperature where the system relaxation time changes intersecting the instrumental resolution time.

CONCLUSIONS

We propose a RENS spectrometer concept based on velocity selection of incident neutrons and wide-angle velocity selection of scattered neutrons achieved by the same rotating collimator-type mechanical device with the optimized shape of blades.

GENERAL SIGNIFICANCE

RENS spectrometer is strongly appealing and innovative because of the simultaneous data collection as a function of energy resolution, wide wavevector range and temperature. Such a spectrometer would be the first practical implementation of RENS concept with a broad range of applications in Life Sciences. This article is part of a Special Issue entitled "Science for Life" Guest Editor: Dr. Austen Angell, Dr. Salvatore Magazù and Dr. Federica Migliardo.

Competition enhances stochasticity in biochemical reactions

We study stochastic dynamics of two competing complexation reactions (i) A + B↔AB and (ii) A + C↔AC. Such reactions are common in biology where different reactants compete for common resources--examples range from binding enzyme kinetics to gene expression. On the other hand, stochasticity is inherent in biological systems due to small copy numbers. We investigate the complex interplay between competition and stochasticity, using coupled complexation reactions as the model system. Within the master equation formalism, we compute the exact distribution of the number of complexes to analyze equilibrium fluctuations of several observables. Our study reveals that the presence of competition offered by one reaction (say A + C↔AC) can significantly enhance the fluctuation in the other (A + B↔AB). We provide detailed quantitative estimates of this enhanced fluctuation for different combinations of rate constants and numbers of reactant molecules that are typical in biology. We notice that fluctuations can be significant even when two of the reactant molecules (say B and C) are infinite in number, maintaining a fixed stoichiometry, while the other reactant (A) is finite. This is purely due to the coupling mediated via resource sharing and is in stark contrast to the single reaction scenario, where large numbers of one of the components ensure zero fluctuation. Our detailed analysis further highlights regions where numerical estimates of mass action solutions can differ from the actual averages. These observations indicate that averages can be a poor representation of the system, hence analysis that is purely based on averages such as mass action laws can be potentially misleading in such noisy biological systems. We believe that the exhaustive study presented here will provide qualitative and quantitative insights into the role of noise and its enhancement in the presence of competition that will be relevant in many biological settings.

Intrinsic mean-square displacements in proteins

The thermal mean-square displacement (MSD) of hydrogen in proteins and its associated hydration water is measured by neutron scattering experiments and used an indicator of protein function. The observed MSD as currently determined depends on the energy resolution width of the neutron scattering instrument employed. We propose a method for obtaining the intrinsic MSD of H in the proteins, one that is independent of the instrument resolution width. The intrinsic MSD is defined as the infinite time value of (r(2)) that appears in the Debye-Waller factor. The method consists of fitting a model to the resolution broadened elastic incoherent structure factor or to the resolution dependent MSD. The model contains the intrinsic MSD, the instrument resolution width, and a rate constant characterizing the motions of H in the protein. The method is illustrated by obtaining the intrinsic MSD (r(2)) of heparan sulphate (HS-0.4), ribonuclease A, and staphysloccal nuclase (SNase) from data in the literature.

Three classes of motion in the dynamic neutron-scattering susceptibility of a globular protein

A simplified description of the 295 K dynamics of a globular protein over a wide frequency range (1-1000 GHz) is obtained by combining neutron scattering of lysozyme with molecular dynamics simulation. The molecular dynamics simulation agrees quantitatively with experiment for both the protein and the hydration water and shows that, whereas the hydration water molecules subdiffuse, the protein atoms undergo confined motion decomposable into three distinct classes: localized diffusion, methyl group rotations, and jumps. Each of the three classes gives rise to a characteristic neutron susceptibility signal.