Large Biological Systems Research Articles

Coarse-grained implicit solvent lipid force field with a compatible resolution to the Cα protein representation.

Biological membranes have been prominent targets for coarse-grained (CG) molecular dynamics simulations. While minimal CG lipid models with three beads per lipid and quantitative CG lipid models with >10 beads per lipid have been well studied, in between them, CG lipid models with a compatible resolution to residue-level CG protein models are much less developed. Here, we extended a previously developed three-bead lipid model into a five-bead model and parameterized it for two phospholipids, POPC (1-palmitoyl-2-oleoyl-sn-glycero-3-phosphocholine) and DPPC (1,2-dipalmitoyl-sn-glycero-3-phosphatidylcholine). The developed model, iSoLF, reproduced the area per lipid, hydrophobic thickness, and phase behaviors of the target phospholipid bilayer membranes at the physiological temperature. The model POPC and DPPC membranes were in liquid and gel phases, respectively, in accordance with experiments. We further examined the spontaneous formation of a membrane bilayer, the temperature dependence of physical properties, the vesicle dynamics, and the POPC/DPPC two-component membrane dynamics of the CG lipid model, showing some promise. Once combined with standard Cα protein models, the iSoLF model will be a powerful tool to simulate large biological membrane systems made of lipids and proteins.

Hierarchical database management model with uncertain parameters

Decision making in large technical, biological, economic and other systems always requires the creation of a complex information system. This implies the need to create sophisticated software for the safe storage of information, its updating and management. At the same time, there should be a convenient and easy to use interface that provides the user with all the necessary functions without unnecessary actions. In conditions of uncertainty, the volume of information becomes even greater. A central coordination system must exist to avoid data inconsistencies and redundancies and to increase the reliability of information storage in the database management system (DBMS). In this article, we propose using a database with a hierarchical structure. In such databases, it is possible to quickly update information at each level separately, without accumulating excessive amounts of information for the entire system.

Exchange Repulsion in Quantum Mechanical/Effective Fragment Potential Excitation Energies: Beyond Polarizable Embedding.

Hybrid quantum mechanical and molecular mechanical (QM/MM) approaches facilitate computational modeling of large biological and materials systems. Typically, in QM/MM, a small region of the system is modeled with an accurate quantum mechanical method and its surroundings with a more efficient alternative, such as a classical force field or the effective fragment potential (EFP). The reliability of QM/MM calculations depends largely on the treatment of interactions between the two subregions, also known as embedding. The polarizable embedding, which allows mutual polarization between solvent and solute, is considered to be essential for describing electronic excitations in polar solvents. In this work, we employ the QM/EFP model and extend the polarizable embedding by incorporating two short-range terms-a charge penetration correction to the electrostatic term and the exchange-repulsion term-both of which are modeled with one-electron contributions to the quantum Hamiltonian. We evaluate the accuracy of these terms by computing excitation energies across 37 molecular clusters consisting of biologically relevant chromophores surrounded by polar solvent molecules. QM/EFP excitation energies are compared to the fully quantum mechanical calculations with the configuration interaction singles (CIS) method. We find that the charge penetration correction diminishes the accuracy of the QM/EFP calculations. On the other hand, while the effect of exchange-repulsion is negligible for most ππ* transitions, the exchange-repulsion significantly improves description of nπ* transitions with blue solvatochromic shifts. As a result, addition of the exchange-repulsion term improves the overall accuracy of QM/EFP. Performances of QM/EFP models remain similar when excitation energies are modeled with cc-pVDZ and aug-cc-pVDZ basis sets.

Coarse-Grained Models of RNA Nanotubes for Large Time Scale Studies in Biomedical Applications.

In order to describe the physical properties of large time scale biological systems, coarse-grained models play an increasingly important role. In this paper we develop Coarse-Grained (CG) models for RNA nanotubes and then, by using Molecular Dynamics (MD) simulation, we study their physical properties. Our exemplifications include RNA nanotubes of 40 nm long, equivalent to 10 RNA nanorings connected in series. The developed methodology is based on a coarse-grained representation of RNA nanotubes, where each coarse bead represents a group of atoms. By decreasing computation cost, this allows us to make computations feasible for realistic structures of interest. In particular, for the developed coarse-grained models with three bead approximations, we calculate the histograms for the bond angles and the dihedral angles. From the dihedral angle histograms, we analyze the characteristics of the links used to build the nanotubes. Furthermore, we also calculate the bead distances along the chains of RNA strands in the nanoclusters. The variations in these features with the size of the nanotube are discussed in detail. Finally, we present the results on the calculation of the root mean square deviations for a developed RNA nanotube to demonstrate the equilibration of the systems for drug delivery and other biomedical applications such as medical imaging and tissue engineering.

Accurate Scoring in Seconds with the Fragment Molecular Orbital and Density-Functional Tight-Binding Methods.

The accurate evaluation of receptor-ligand interactions is an essential part of rational drug design. While quantum mechanical (QM) methods have been a promising means by which to achieve this, traditional QM is not applicable for large biological systems due to its high computational cost. Here, the fragment molecular orbital (FMO) method has been combined with the density-functional tight-binding (DFTB) method to compute energy calculations of biological systems in seconds. FMO-DFTB outperformed GBVI/WSA in identifying a set of 10 binders versus a background of 500 decoys applied to human k-opioid receptor. The significant increase in the speed and the high accuracy achieved with FMO-DFTB calculations allows FMO to be applied in areas of drug discovery that were not previously accessible to traditional QM methodologies. For the first time, it is now possible to perform FMO calculations in a high-throughput manner.

Free Energies of the Disassembly of Viral Capsids from a Multiscale Molecular Simulation Approach.

Molecular simulations of large biological systems, such as viral capsids, remains a challenging task in soft matter research. On one hand, coarse-grained (CG) models attempt to make the description of the entire viral capsid disassembly feasible. On the other hand, the permanent development of novel molecular dynamics (MD) simulation approaches, like enhanced sampling methods, attempt to overcome the large time scales required for such simulations. Those methods have a potential for delivering molecular structures and properties of biological systems. Nonetheless, exploring the process on how a viral capsid disassembles by all-atom MD simulations has been rarely attempted. Here, we propose a methodology to analyze the disassembly process of viral capsids from a free energy perspective, through an efficient combination of dynamics using coarse-grained models and Poisson-Boltzmann simulations. In particular, we look at the effect of pH and charge of the genetic material inside the capsid, and compute the free energy of a disassembly trajectory precalculated using CG simulations with the SIRAH force field. We used our multiscale approach on the Triatoma virus (TrV) as a test case, and find that even though an alkaline environment enhances the stability of the capsid, the resulting deprotonation of the genetic material generates a Coulomb-type electrostatic repulsion that triggers disassembly.

Sensitivity boosts by the CPMAS CryoProbe for challenging biological assemblies

Despite breakthroughs in MAS NMR hardware and experimental methodologies, sensitivity remains a major challenge for large and complex biological systems. Here, we report that 3–4 fold higher sensitivities can be obtained in heteronuclear-detected experiments, using a novel HCN CPMAS probe, where the sample coil and the electronics operate at cryogenic temperatures, while the sample is maintained at ambient temperatures (BioSolids CryoProbe™). Such intensity enhancements permit recording 2D and 3D experiments that are otherwise time-prohibitive, such as 2D 15N-15N proton-driven spin diffusion and 15N-13C double cross polarization to natural abundance carbon experiments. The benefits of CPMAS CryoProbe-based experiments are illustrated for assemblies of kinesin Kif5b with microtubules, HIV-1 capsid protein assemblies, and fibrils of human Y145Stop and fungal HET-s prion proteins – demanding systems for conventional MAS solid-state NMR and excellent reference systems in terms of spectral quality. We envision that this probe technology will be beneficial for a wide range of applications, especially for biological systems suffering from low intrinsic sensitivity and at physiological temperatures.

Smeared Multiscale Finite Element Models for Mass Transport and Electrophysiology Coupled to Muscle Mechanics

Mass transport represents the most fundamental process in living organisms. It includes delivery of nutrients, oxygen, drugs, and other substances from the vascular system to tissue and transport of waste and other products from cells back to vascular and lymphatic network and organs. Furthermore, movement is achieved by mechanical forces generated by muscles in coordination with the nervous system. The signals coming from the brain, which have the character of electrical waves, produce activation within muscle cells. Therefore, from a physics perspective, there exist a number of physical fields within the body, such as velocities of transport, pressures, concentrations of substances, and electrical potential, which is directly coupled to biochemical processes of transforming the chemical into mechanical energy and further internal forces for motion. The overall problems of mass transport and electrophysiology coupled to mechanics can be investigated theoretically by developing appropriate computational models. Due to the enormous complexity of the biological system, it would be almost impossible to establish a detailed computational model for the physical fields related to mass transport, electrophysiology, and coupled fields. To make computational models feasible for applications, we here summarize a concept of smeared physical fields, with coupling among them, and muscle mechanics, which includes dependence on the electrical potential. Accuracy of the smeared computational models, also with coupling to muscle mechanics, is illustrated with simple example, while their applicability is demonstrated on a liver model with tumors present. The last example shows that the introduced methodology is applicable to large biological systems.

Feasibility of trifluoromethyl TROSY NMR at high magnetic fields.

Insights into the structure and dynamics of large biological systems has been greatly improved by two concurrent NMR approaches: the application of transverse relaxation-optimized spectroscopy (TROSY) techniques in multi-dimensional NMR, especially the methyl-TROSY, and the resurgence of 19F NMR using trifluoromethyl (CF3) probes. Herein we investigate the feasibility of combining these approaches into a trifluoromethyl-TROSY experiment. Using a CF3-labelled parvalbumin, we have evaluated the natural abundance 13C-19F correlation spectra and find no indication of a CF3 TROSY at high magnetic fields.

Planar AFM macro-probes to study the biomechanical properties of large cells and 3D cell spheroids

The ability to measure mechanical response of cells under applied load is essential for developing more accurate models of cell mechanics and mechanotransduction. Living cells have been mechanically investigated by several approaches. Among them, atomic force microscopy (AFM) is widely used thanks to its high versatility and sensitivity. In the case of large cells or 3D multicellular aggregates, standard AFM probes may not be appropriate to investigate the mechanical properties of the whole biological system. Owing to their size, standard AFM probes can compress only a single somatic cell or part of it. To fill this gap, we have designed and fabricated planar AFM macro-probes compatible with commercial AFM instruments. The probes are constituted of a large flat compression plate, connected to the chip by two flexible arms, whose mechanical characteristics are tuned for specific biological applications. As proof of concept, we have used the macro-probes to measure the viscoelasticity of large spherical biological systems, which have a diameter above 100 μm: human oocytes and 3D cell spheroids. Compression experiments are combined with visual inspection, using a side-view configuration imaging, which allows us to monitor the sample morphology during the compression and to correlate it with the viscoelastic parameters. Our measurements provide a quantitative estimate of the relaxation times of such biological systems, which are discussed in relation to data present in literature. The broad applicability of the AFM macro-probes can be relevant to study the biomechanical features in any biological process involving large soft materials. Statement of SignificanceThe understanding of the role of physical factors in defining cell and tissue functions requires to develop new methods or improve the existing ones to accurately measure the biomechanical properties. AFM is a sensitive and versatile tool to measure the mechanical features from single proteins to single cells. When cells or cell aggregates exceed few tens of microns, AFM suffers from limitations. On these biological systems the control of the contact area and the application of a precise uniform compression becomes crucial. A modification of the standard cantilevers fabrication allowed us obtaining AFM macro-probes, having large planar contact area and spring constant suitable for biological investigations. They were demonstrated valuable to characterize the mechanical properties of large hierarchical biological systems.

Heterogeneous CPU+GPU-Enabled Simulations for DFTB Molecular Dynamics of Large Chemical and Biological Systems.

We introduce a new heterogeneous CPU+GPU-enhanced DFTB approach for the routine and efficient simulation of large chemical and biological systems. Compared to homogeneous computing with conventional CPUs, heterogeneous computing approaches exhibit substantial performance with only a modest increase in power consumption, both of which are essential to upcoming exascale computing initiatives. We show that DFTB-based molecular dynamics is a natural candidate for heterogeneous computing, since the computational bottleneck in these simulations is the diagonalization of the Hamiltonian matrix, which is performed several times during a single molecular dynamics trajectory. To thoroughly test and understand the performance of our heterogeneous CPU+GPU approach, we examine a variety of algorithmic implementations, benchmarks of different hardware configurations, and applications of this methodology on several large chemical and biological systems. Finally, to demonstrate the capability of our implementation, we conclude with a large-scale DFTB MD simulation of explicitly solvated HIV protease (3974 atoms total) as a proof-of-concept example of an extremely large/complex system which, to the best of our knowledge, is the first time that an entire explicitly solvated protein has been treated at a quantum-based MD level of detail.

Aromatic 19F-13C TROSY: a background-free approach to probe biomolecular structure, function, and dynamics.

Obtaining atomic level information about the structure and dynamics of biomolecules is critical to understand their function. Nuclear magnetic resonance (NMR) spectroscopy provides unique insights into the dynamic nature of biomolecules and their interactions, capturing transient conformers and their features. However, relaxation-induced line broadening and signal overlap make it challenging to apply NMR to large biological systems. Here, we take advantage of the high sensitivity and the broad chemical-shift range of 19F nuclei, and leverage the remarkable relaxation properties of the aromatic 19F-13C spin pair to disperse 19F resonances in a 2-dimensional transverse relaxation optimized TROSY spectrum. We demonstrate the application of the 19F-13C TROSY to investigate proteins and nucleic acids. This experiment expands the scope of 19F NMR in the study of structure, dynamics and function of large and complex biological systems and provides a powerful background-free NMR probe.

GPU Accelerated Quantum Virtual Screening: Application for the Natural Inhibitors of New Dehli Metalloprotein (NDM-1).

Quantum mechanical approaches for the massive computation on large biological system such as virtual screening in drug design and development have presented a challenge to computational chemists for many years. In this study, we demonstrated that by taking advantage of rapid growth of GPU-based hardware and software (i.e., teraChem), it is feasible to perform virtual screening of a refined chemical library at quantum mechanical level in order to identify the lead compounds with improved accuracy, especially for the drug targets such as metalloproteins in which significant charge transfer and polarization occur amongst the metal ions and their coordinated amino acids. Our calculations predicted four nature compounds (i.e., Curcumin, Catechin, menthol, and Ferulic acid) as the suitable inhibitors for antibiotics resistance against New Delhi Metallo-β-lactamase-1 (NDM-1). Molecular orbitals (MOs) of the QM region of metal ions and their coordinated residues indicate that the bridged hydroxide ion delocalized the electron over the Zn-OH-Zn group at HOMO, different from MOs when the OH− is not presented in NDM-1. This indicates that the bridged hydroxide ion plays an important role in the design of antibiotics and other inhibitors targeting the metalloproteins.

Nonlinear-response properties in a simplified time-dependent density functional theory (sTD-DFT) framework: Evaluation of the first hyperpolarizability.

Recent developments in nonlinear imaging microscopy show the need to implement new theoretical tools, which are able to characterize nonlinear optical properties in an efficient way. For second-harmonic imaging microscopy (SHIM), quantum chemistry could play an important role to design new exogenous dyes with enhanced first hyperpolarizabilities or to characterize the response origin in large endogenous biological systems. Such methods should be able to screen a large number of compounds while reproducing their trends and to treat large systems in reasonable computation times. To fulfill these requirements, we present a new simplified time-dependent density functional theory (sTD-DFT) implementation to evaluate the first hyperpolarizability where the Coulomb and exchange integrals are approximated by short-range damped Coulomb interactions of transition density monopoles. For an ultra-fast computation of the first hyperpolarizability, a tight-binding version (sTD-DFT-xTB) is also proposed. In our implementation, a sTD-DFT calculation is more than 600 time faster with respect to a regular TD-DFT treatment, while the xTB version speeds up the entire calculation further by at least two orders of magnitude. We challenge our implementation on three test cases: typical push-pull π-conjugated compounds, fluorescent proteins, and a collagen model, which were selected to model requirements for SHIM applications.

Light sheet theta microscopy for rapid high-resolution imaging of large biological samples

BackgroundAdvances in tissue clearing and molecular labeling methods are enabling unprecedented optical access to large intact biological systems. These developments fuel the need for high-speed microscopy approaches to image large samples quantitatively and at high resolution. While light sheet microscopy (LSM), with its high planar imaging speed and low photo-bleaching, can be effective, scaling up to larger imaging volumes has been hindered by the use of orthogonal light sheet illumination.ResultsTo address this fundamental limitation, we have developed light sheet theta microscopy (LSTM), which uniformly illuminates samples from the same side as the detection objective, thereby eliminating limits on lateral dimensions without sacrificing the imaging resolution, depth, and speed. We present a detailed characterization of LSTM, and demonstrate its complementary advantages over LSM for rapid high-resolution quantitative imaging of large intact samples with high uniform quality.ConclusionsThe reported LSTM approach is a significant step for the rapid high-resolution quantitative mapping of the structure and function of very large biological systems, such as a clarified thick coronal slab of human brain and uniformly expanded tissues, and also for rapid volumetric calcium imaging of highly motile animals, such as Hydra, undergoing non-isomorphic body shape changes.

Multiscale smeared finite element model for mass transport in biological tissue: From blood vessels to cells and cellular organelles

One of the basic and vital processes in living organisms is mass exchange, which occurs on several levels: it goes from blood vessels to cells and organelles within cells. On that path, molecules, as oxygen, metabolic products, drugs, etc. Traverse different macro and micro environments – blood, extracellular/intracellular space, and interior of organelles; and also biological barriers such as walls of blood vessels and membranes of cells and organelles. Many aspects of this mass transport remain unknown, particularly the biophysical mechanisms governing drug delivery. The main research approach relies on laboratory and clinical investigations. In parallel, considerable efforts have been directed to develop computational tools for additional insight into the intricate process of mass exchange and transport. Along these lines, we have recently formulated a composite smeared finite element (CSFE) which is composed of the smeared continuum pressure and concentration fields of the capillary and lymphatic system, and of these fields within tissue. The element offers an elegant and simple procedure which opens up new lines of inquiry and can be applied to large systems such as organs and tumors models. Here, we extend this concept to a multiscale scheme which concurrently couples domains that span from large blood vessels, capillaries and lymph, to cell cytosol and further to organelles of nanometer size. These spatial physical domains are coupled by the appropriate connectivity elements representing biological barriers. The composite finite element has “degrees of freedom” which include pressures and concentrations of all compartments of the vessels-tissue assemblage. The overall model uses the standard, measurable material properties of the continuum biological environments and biological barriers. It can be considered as a framework into which we can incorporate various additional effects (such as electrical or biochemical) for transport through membranes or within cells. This concept and the developed FE software within our package PAK offers a computational tool that can be applied to whole-organ systems, while also including specific domains such as tumors. The solved examples demonstrate the accuracy of this model and its applicability to large biological systems.

Homochiral Emissive Λ8 - and Δ8 -[Ir8 Pd4 ]16+ Supramolecular Cages.

Synthetic self‐assembly is a powerful technique for the bottom‐up construction of discrete and well‐defined polyhedral nanostructures resembling the spherical shape of large biological systems. In recent years, numerous Archimedean‐shaped coordination cages have been reported based on the assembly of bent monodentate organic ligands containing two or more distal pyridyl rings and square‐planar PdII ions. The formation of photoactive PdII metallamacrocycles and cages, however, remain rare. Here we report the first examples of emissive and homochiral supramolecular cages of the form [Ir8Pd4]16+. These cages provide a suitably sized cavity to host large guest molecules. Importantly, encapsulation and energy transfer have been observed between the blue‐emitting NBu4[Ir(dFppy)2(CN)2] guest and the red‐emitting Δ8‐[Ir8Pd4]16+ cage.

Role and underlying mechanisms of the interstitial protein periostin in the diagnosis and treatment of malignant tumors (Review)

Invasion and metastasis are the major characteristics of malignant tumors and are complex processes involving multiple genes. Gene regulation is a precise, large and complex biological control system, and its underlying mechanisms remain to be elucidated. Mesenchymal-specific genes are expressed primarily by mesenchymal cells, and the expression products of these genes are molecules with various structures and functions, including secreted proteins and extracellular matrix proteins. The periostin gene has been newly identified as a mesenchymal-specific gene and an extracellular-matrix secreted protein. Periostin is able to bind to various subtypes of integrin receptors on the surface of the cell membrane. This triggers relevant signal transduction pathways to alter the microenvironment of cancer cells in order to facilitate their survival, invasion, metastasis and angiogenesis as well as enhance the tolerance to hypoxia and chemicals. Therefore, periostin is associated with the grade of malignancy, level of invasion and prognosis of malignant tumors. The in-depth study of periostin may provide an effective marker for tumor diagnosis and prognosis, as well as a novel treatment target.

Rapid and accurate assessment of GPCR–ligand interactions Using the fragment molecular orbital‐based density‐functional tight‐binding method

The reliable and precise evaluation of receptor–ligand interactions and pair‐interaction energy is an essential element of rational drug design. While quantum mechanical (QM) methods have been a promising means by which to achieve this, traditional QM is not applicable for large biological systems due to its high computational cost. Here, the fragment molecular orbital (FMO) method has been used to accelerate QM calculations, and by combining FMO with the density‐functional tight‐binding (DFTB) method we are able to decrease computational cost 1000 times, achieving results in seconds, instead of hours. We have applied FMO‐DFTB to three different GPCR–ligand systems. Our results correlate well with site directed mutagenesis data and findings presented in the published literature, demonstrating that FMO‐DFTB is a rapid and accurate means of GPCR–ligand interactions. © 2017 Authors. Journal of Computational Chemistry Published by Wiley Periodicals, Inc.

The Emergence MAC (E-MAC) protocol for wireless sensor networks

Large scale biological systems often exhibit emergent properties that are attractive in an engineering context. In this paper, the context is a class of wireless sensor networks for emergency environmental monitoring. The attractive properties are simplicity, self-organisation, adaptiveness to scenario change and a lack of scenario-specific parameter tunings. Emergence Medium Access Control (E-MAC) is a scheme inspired by biological social populations that individually react to environmental stimuli. Using a very simple protocol, it exhibits the desired emergent properties. When compared to a well established practical counterpart, the IEEE 802.11 CSMA/CA standard, it exhibits better throughput, end-to-end delay and fairness. This paper describes the motivation and design of E-MAC, and presents the above comparison.