Single-molecule biophysics

Fine-Grained Parallel and Distributed Spatial Stochastic Simulation of Biological Reactions

Recent reports on biomaterials and biological systems at nano scale provide researchers with a fertile ground with regard to materials, enabling bioelectronics, bio sensing and new nanotechnologies that cover a wide range of applications. The signal transductions have been reported for many biological phenomenons and new field of biophysics namely Biosensors and Bioelectronics have been emerged out. The advances in the study of various aspects of bio molecules like electrical, optical, thermal etc has established the interesting area of research like biophotonics, nanobiotechnology, molecular solid, molecular liquids, bio instrumentation etc. The present study discusses the some aspects and applications of the bioprocess yields nanostructures that are nearly flawless in composition, stereo specific in structure, and flexible. Furthermore, these biomaterials are environment friendly because they are biodegradable in nature. Biological compounds are self assembled into complex nanostructures and behave like a system possessing long range hierarchical nanoscale order. In addition, chemical modification and genetic engineering can be used to modify bio materials to enhance a specific property. Various biomaterials have been reported which allow nanostructure control for nano photonic applications. The dielectric and conduction properties of the bio molecules have been the subject of many investigations. As a result, there exist a wealth of valuable information on the charge transport and rotational properties of many bio molecules. Amino acids and proteins, nucleic acids, lipids, cell and tissues have been characterized over a wide frequency spectrum ranging from a few hertz to Giga hertz. In certain cases, dielectric measurements have been exploited to probe the physical changes taking place in biologically important structures, for example, in lipid phase transition process in membrane. The phase transition in membrane may be analyzed by applying the theory for lyotropic phase transition in liquid crystals. The photosynthesis property in plant systems may be well interpreted by exploiting the theory for excitonic process taking place in organic semiconductors for electroluminescence and photovoltaic. The biosensor for the measurement of compatibility of a graft union based on electrical measurements has been reported. The present paper discusses the some aspects of recent advances in biomaterials research and correlates it as a basis of emergence of a new discipline namely Bioelectronics and Bio photonics.

Interfacial nanoarchitectonics for molecular manipulation and molecular machine operation

Characterizing thermodynamics and kinetics of molecular systems is the ultimate goal of biophysics. In drug discovery, this information becomes essential. Understanding local and global rearrangements, how formation and disruption of biomolecular complexes occur, the molecular determinants involved and the preferred pathways followed, contribute to forming a solid ground for the development of new drugs. Quantifying specific kinetic parameters, such as off rates and the closely related residence time, is increasingly being incorporated in the drug optimization phase. Several experimental techniques established to study and quantify kinetic features. Conversely, the computational counterpart still faces severe challenges, such as accessing the time scales at which these slow events occur, while acquiring acceptable statistics. During this PhD program, we explored current, state-of-the-art computational methods, and combination thereof, to study kinetic properties of pharmaceutically relevant biomolecules. In particular, we applied different protocols to three test systems. In the first case, we reconstructed the free energy surface of an intrinsically disordered protein and calculated interconversion rates between the differently folded states identified. In the second application, Markov State Models were employed to identify relevant states along the protein-ligand binding pathway. Using these states as a template, a putative pathway on which computing the free energy profile associated with the binding process was determined. As for the third test case, we performed unbinding simulations on a series of ligands and prioritized them according to their average computational unbinding time. The obtained ranking was subsequently confirmed by performing experimental assays. Despite clear limitations, the picture arising from the studies was encouraging. Computer simulations emerged undoubtedly as a valuable instrument for assessing kinetic properties of biomolecular systems. Therefore, in light of the rapid advances in computer power expected from the upcoming years, their role as effective tools to assist the discovery of novel drug-like molecules is extremely promising.

Integral equation theory (IET) provides an effective solvation model for chemical and biological systems that balances computational efficiency and accuracy. We present a new software package, the expanded package for IET-based solvation (EPISOL), that performs 3D-reference interaction site model (3D-RISM) calculations to obtain the solvation structure and free energies of solute molecules in different solvents. In EPISOL, we have implemented 22 different closures, multiple free energy functionals, and new variations of 3D-RISM theory, including the recent hydrophobicity-induced density inhomogeneity (HI) theory for hydrophobic solutes and ion-dipole correction (IDC) theory for negatively charged solutes. To speed up the convergence and enhance the stability of the self-consistent iterations, we have introduced several numerical schemes in EPISOL, including a newly developed dynamic mixing approach. We show that these schemes have significantly reduced the failure rate of 3D-RISM calculations compared to AMBER-RISM software. EPISOL consists of both a user-friendly graphic interface and a kernel library that allows users to call its routines and adapt them to other programs. EPISOL is compatible with the force-field and coordinate files from both AMBER and GROMACS simulation packages. Moreover, EPISOL is equipped with an internal memory control to efficiently manage the use of physical memory, making it suitable for performing calculations on large biomolecules. We demonstrate that EPISOL can efficiently and accurately calculate solvation density distributions around various solute molecules (including a protein chaperone consisting of 120,715 atoms) and obtain solvent free energy for a wide range of organic compounds. We expect that EPISOL can be widely applied as a solvation model for chemical and biological systems. EPISOL is available at https://github.com/EPISOLrelease/EPISOL.

Although proteins generally fold to their thermodynamically most stable state, some metastable proteins populate higher free energy states. Conformational changes from metastable higher free energy states to lower free energy states with greater stability can then generate the work required to perform physiologically important functions. However, how metastable proteins fold to these higher free energy states in the cell and avoid more stable but inactive conformations is poorly understood. The serpin family of metastable protease inhibitors uses large conformational changes that are downhill in free energy to inhibit target proteases by pulling apart the protease active site. The serpin antithrombin III (ATIII) targets thrombin and other proteases involved in blood coagulation, and ATIII misfolding can thus lead to thrombosis and other diseases. ATIII has three disulfide bonds, two near the N terminus and one near the C terminus. Our studies of ATIII in-cell folding reveal a surprising, biased order of disulfide bond formation, with early formation of the C-terminal disulfide, before formation of the N-terminal disulfides, critical for folding to the active, metastable state. Early folding of the predominantly β-sheet ATIII domain in this two-domain protein constrains the reactive center loop (RCL), which contains the protease-binding site, ensuring that the RCL remains accessible. N-linked glycans and carbohydrate-binding molecular chaperones contribute to the efficient folding and secretion of functional ATIII. The inability of a number of disease-associated ATIII variants to navigate the folding reaction helps to explain their disease phenotypes.

Single-molecule biophysics has transformed our understanding of biology, but also of the physics of life. More exotic than simple soft matter, biomatter lives far from thermal equilibrium, covering multiple lengths from the nanoscale of single molecules to up to several orders of magnitude higher in cells, tissues and organisms. Biomolecules are often characterized by underlying instability: multiple metastable free energy states exist, separated by levels of just a few multiples of the thermal energy scale kBT, where kB is the Boltzmann constant and T absolute temperature, implying complex inter-conversion kinetics in the relatively hot, wet environment of active biological matter. A key benefit of single-molecule biophysics techniques is their ability to probe heterogeneity of free energy states across a molecular population, too challenging in general for conventional ensemble average approaches. Parallel developments in experimental and computational techniques have catalysed the birth of multiplexed, correlative techniques to tackle previously intractable biological questions. Experimentally, progress has been driven by improvements in sensitivity and speed of detectors, and the stability and efficiency of light sources, probes and microfluidics. We discuss the motivation and requirements for these recent experiments, including the underpinning mathematics. These methods are broadly divided into tools which detect molecules and those which manipulate them. For the former we discuss the progress of super-resolution microscopy, transformative for addressing many longstanding questions in the life sciences, and for the latter we include progress in ‘force spectroscopy’ techniques that mechanically perturb molecules. We also consider in silico progress of single-molecule computational physics, and how simulation and experimentation may be drawn together to give a more complete understanding. Increasingly, combinatorial techniques are now used, including correlative atomic force microscopy and fluorescence imaging, to probe questions closer to native physiological behaviour. We identify the trade-offs, limitations and applications of these techniques, and discuss exciting new directions.

Giorgio Careri was consumed by two different ideas about how biomolecules function. He thought that energy transport in proteins was mediated by solitons. Separately, he proposed that protein function was controlled by a network of water molecules, with a density above a critical percolation threshold. He was wrong about the first idea. He was right about the second, but perhaps not quite in the way he imagined it. The statement that “water is important to biomolecules” is so obvious that it seems pointless to even make it, let alone to set aside a special issue of the Journal of Biological Physics on the topic. Of course water is important for biological systems. We learned this in elementary school, and this is why scientists searching for life on Mars look for tell-tale evidence of water. What is so great about asserting such a manifestly self-evident statement? In the field of biological physics, we have only now begun to understand the many marvelously different ways in which water can influence the function of biomolecules. The experimental genesis of these ideas is in the early work of Frauenfelder and collaborators, and in the work of Careri and coworkers. The review by Pascale Mentre [1] in this issue provides a succinct account of the role of water in the orchestration of cell machinery. The review also corrects many misunderstandings. The central ideas are that (i) interfacial water modulates protein function, and (ii) nanoconfined water is so different from bulk water that one cannot use simply use the statistical physics models developed for bulk water. We now also know that there are actually special water molecules that directly participate in protein function. An example of such a special water molecule is in the exciting report on the detection of a special hydrogen-bonded water molecule in the proton pump archaerhodospin-3, by the Rothschild group (Saint Clair et al. [2]). Modern spectroscopic methods continue to advance (see for example the paper on terahertz spectroscopy of water nanoclusters by Johnson [3] in this issue). We expect that this discovery of special water molecules will not be isolated. From an evolutionary point of view, it is logical that some proteins have evolved to take advantage of special water molecules to assist in function, in addition to the interfacial water that inspired Careri. The single most exciting addition to the toolkit that is available to biological physicists today involves computational models and methods aimed directly at understanding water. As Fabio Bruni [4] writes in his personal memoir, Careri was singularly uncomfortable with computers. It is therefore interesting that modern computational methods may eventually provide strong support for the role of interfacial nanoconfined water in the functioning of biomolecules. There is not a single accepted computational model of water. The paper by Herzfeld and collaborators [5] describes a tractable and efficient new simulation model for dissociable water in nanoclusters and chains of water. Kumar and Keyes have developed one of the best molecular models for understanding the infrared spectra of water molecules by careful consideration of water in the first hydration shell [6]. Strekalova et al. have studied the effect of a hydrophobic environment, such as one might expect in protein pockets, on a hypothesized critical point in nanoconfined water [7]. The papers suggest the strong vitality inherent in the computational approach, which also provides new insights into the nature of the dynamics of water. One of the most vigorous arguments in the physics of water today involves the nature of the dynamics of water, whether the dynamics are similar to those observed in glassy systems, or whether there is a liquid-critical point. A combination of computational and spectroscopic studies should get us closer to an answer. Perhaps the most interesting new insight may simply be this: we have known that water is essential for structure. It is required for proteins to fold properly. We are now learning that water also strongly influences dynamics. New insights based on a combination of novel forms of spectroscopy, data from coherent X-ray sources, computational insights, and new theoretical ideas borrowed from glass transitions and critical phenomena, all have provided firm support to the idea that proteins need to be dynamic in order to function properly, and that protein dynamics are strongly controlled by the dynamic properties of water. We would like to thank especially our co-editor Feng Wang. Thanks also go to Brigita Urbanc, and to students in Gene Stanley’s group at Boston University. We gratefully acknowledge the contributions of the authors of the articles in this special issue, and to the anonymous reviewers who set aside valuable time selflessly. A final thanks to Sonya Bahar, Rudi Podgornik, especially to Maria Bellantone for her inspiration, and to Ruel Pinero and Mieke van der Fluit for their patience.

Quantifying entropy production in various active matter phases will open new avenues for probing self-organization principles in these far-from-equilibrium systems. It has been hypothesized that the dissipation of free energy by active matter systems may be optimized, leading to system trajectories with histories of large dissipation and an accompanying emergence of ordered dynamical states. This interesting idea has not been widely tested. In particular, it is not clear whether emergent states of actomyosin networks, which represent a salient example of biological active matter, self-organize following the principle of dissipation optimization. In order to start addressing this question using detailed computational modelling, we rely on the MEDYAN simulation platform, which allows simulating active matter networks from fundamental molecular principles. We have extended the capabilities of MEDYAN to allow quantification of the rates of dissipation resulting from chemical reactions and relaxation of mechanical stresses during simulation trajectories. This is done by computing precise changes in Gibbs free energy accompanying chemical reactions using a novel formula and through detailed calculations of instantaneous values of the system’s mechanical energy. We validate our approach with a mean-field model that estimates the rates of dissipation from filament treadmilling. Applying this methodology to the self-organization of small disordered actomyosin networks, we find that compact and highly cross-linked networks tend to allow more efficient transduction of chemical free energy into mechanical energy. In these simple systems, we observe that spontaneous network reorganizations tend to result in a decrease in the total dissipation rate to a low steady-state value. Future studies might carefully test whether the dissipation-driven adaptation hypothesis applies in this instance, as well as in more complex cytoskeletal geometries.

Single Molecule Biology

Molecular machines transduce free energy between different forms throughout all living organisms. Unlike their macroscopic counterparts, molecular machines are characterized by stochastic fluctuations, overdamped dynamics, and soft components, and operate far from thermodynamic equilibrium. In addition, information is a relevant free energy resource for molecular machines, leading to new modes of operation for nanoscale engines. Toward the objective of engineering synthetic nanomachines, an important goal is to understand how molecular machines transduce free energy to perform their functions in biological systems. In this review, we discuss the nonequilibrium thermodynamics of free energy transduction within molecular machines, with a focus on quantifying energy and information flows between their components. We review results from theory, modeling, and inference from experiments that shed light on the internal thermodynamics of molecular machines, and ultimately explore what we can learn from considering these interactions.

Self-propelled particles are found in many biological systems as well as in numerous synthetic systems where self-motile colloids and artificial swimmers have recently been realized. These active systems exhibit a variety of process not found in equilibrium systems. Most studies of active matter have been performed with smooth landscapes; however, there is an increasing amount of work on active matter coupled to ordered or disordered substrates. Due to the size scale of the active particles, suitable random, periodic, or quasiperiodic substrates could be made optically. Here we present recent results for active matter on periodic substrates and discuss some future directions. We also enumerate many of the active matter versions of nonactive systems that could be realized with periodic substrates, including an active matter glass, commensurate-incommensurate transitions, solitons, and sliding states. We show that the driven dynamics of active matter can produce directional locking on periodic substrates. Finally, we discuss the possibility of introducing a dynamical substrate in order to create active matter versions of classical time crystals.

Active matter has played a pivotal role in advancing understanding of non-equilibrium systems, leading to a fundamental shift in the study of biophysical phenomena. The foundation of active matter research is built on assumptions regarding the symmetry of microscopic constituents. While these assumptions have been validated extensively, instances of mixed or joint symmetries are prevalent in biological systems. This review explores the coexistence of polar and nematic order in active matter, emphasizing the theoretical and experimental challenges associated with these systems. By integrating insights from recent studies, we highlight the importance of considering mixed symmetries to accurately describe biological processes. This exploration not only benefits the field of biology but could also open new horizons for non-equilibrium physics, offering a comprehensive framework for understanding complex behavior in active matter.

Activity and autonomous motion are fundamental in living and engineering systems. This has stimulated the new field of ‘active matter’ in recent years, which focuses on the physical aspects of propulsion mechanisms, and on motility-induced emergent collective behavior of a larger number of identical agents. The scale of agents ranges from nanomotors and microswimmers, to cells, fish, birds, and people. Inspired by biological microswimmers, various designs of autonomous synthetic nano- and micromachines have been proposed. Such machines provide the basis for multifunctional, highly responsive, intelligent (artificial) active materials, which exhibit emergent behavior and the ability to perform tasks in response to external stimuli. A major challenge for understanding and designing active matter is their inherent nonequilibrium nature due to persistent energy consumption, which invalidates equilibrium concepts such as free energy, detailed balance, and time-reversal symmetry. Unraveling, predicting, and controlling the behavior of active matter is a truly interdisciplinary endeavor at the interface of biology, chemistry, ecology, engineering, mathematics, and physics.The vast complexity of phenomena and mechanisms involved in the self-organization and dynamics of motile active matter comprises a major challenge. Hence, to advance, and eventually reach a comprehensive understanding, this important research area requires a concerted, synergetic approach of the various disciplines. The 2020 motile active matter roadmap of Journal of Physics: Condensed Matter addresses the current state of the art of the field and provides guidance for both students as well as established scientists in their efforts to advance this fascinating area.

Chemical basis of interactions between engineered nanoparticles and biological systems.