Charge transport in individual short base stacked single-stranded RNA molecules.

Charge transport in biomolecules is crucial for many biological and technological applications, including biomolecular electronics devices and biosensors. RNA has become the focus of research because of its importance in biomedicine, but its charge transport properties are not well understood. Here, we use the Scanning Tunneling Microscopy-assisted molecular break junction method to measure the electrical conductance of particular 5-base and 10-base single-stranded (ss) RNA sequences capable of base stacking. These ssRNA sequences show single-molecule conductance values around [Formula: see text] ([Formula: see text]), while equivalent-length ssDNAs result in featureless conductance histograms. Circular dichroism (CD) spectra and MD simulations reveal the existence of extended ssRNA conformations versus folded ssDNA conformations, consistent with their different electrical behaviors. Computational molecular modeling and Machine Learning-assisted interpretation of CD data helped us to disentangle the structural and electronic factors underlying CT, thus explaining the observed electrical behavior differences. RNA with a measurable conductance corresponds to sequences with overall extended base-stacking stabilized conformations characterized by lower HOMO energy levels delocalized over a base-stacking mediating CT pathway. In contrast, DNA and a control RNA sequence without significant base-stacking tend to form closed structures and thus are incapable of efficient CT.

Mechanical fatigue testing in silico: Dynamic evolution of material properties of nanoscale biological particles.

Biological particles have evolved to possess mechanical characteristics necessary to carry out their functions. We developed a computational approach to "fatigue testing in silico", in which constant-amplitude cyclic loading is applied to a particle to explore its mechanobiology. We used this approach to describe dynamic evolution of nanomaterial properties and low-cycle fatigue in the thin spherical encapsulin shell, thick spherical Cowpea Chlorotic Mottle Virus (CCMV) capsid, and thick cylindrical microtubule (MT) fragment over 20 cycles of deformation. Changing structures and force-deformation curves enabled us to describe their damage-dependent biomechanics (strength, deformability, stiffness), thermodynamics (released and dissipated energies, enthalpy, and entropy) and material properties (toughness). Thick CCMV and MT particles experience material fatigue due to slow recovery and damage accumulation over 3-5 loading cycles; thin encapsulin shells show little fatigue due to rapid remodeling and limited damage. The results obtained challenge the existing paradigm: damage in biological particles is partially reversible owing to particle's partial recovery; fatigue crack may or may not grow with each loading cycle and may heal; and particles adapt to deformation amplitude and frequency to minimize the energy dissipated. Using crack size to quantitate damage is problematic as several cracks might form simultaneously in a particle. Dynamic evolution of strength, deformability, and stiffness, can be predicted by analyzing the cycle number (N) dependent damage, [Formula: see text] , where α is a power law and Nf is fatigue life. Fatigue testing in silico can now be used to explore damage-induced changes in the material properties of other biological particles. STATEMENT OF SIGNIFICANCE: Biological particles possess mechanical characteristics necessary to perform their functions. We developed "fatigue testing in silico" approach, which employes Langevin Dynamics simulations of constant-amplitude cyclic loading of nanoscale biological particles, to explore dynamic evolution of the mechanical, energetic, and material properties of the thin and thick spherical particles of encapsulin and Cowpea Chlorotic Mottle Virus, and the microtubule filament fragment. Our study of damage growth and fatigue development challenge the existing paradigm. Damage in biological particles is partially reversible as fatigue crack might heal with each loading cycle. Particles adapt to deformation amplitude and frequency to minimize energy dissipation. The evolution of strength, deformability, and stiffness, can be accurately predicted by analyzing the damage growth in particle structure.

Therapeutic phosphorodiamidate morpholino oligonucleotides: Physical properties, solution structures, and folding thermodynamics.

Elucidating the structure-function relationships for therapeutic RNA mimicking phosphorodiamidate morpholino oligonucleotides (PMOs) is challenging due to the lack of information about their structures. While PMOs have been approved by the US Food and Drug Administration for treatment of Duchenne muscular dystrophy, no structural information on these unique, charge-neutral, and stable molecules is available. We performed circular dichroism and solution viscosity measurements combined with molecular dynamics simulations and machine learning to resolve solution structures of 22-mer, 25-mer, and 30-mer length PMOs. The PMO conformational dynamics are defined by the competition between non-polar nucleobases and uncharged phosphorodiamidate groups for shielding from solvent exposure. PMO molecules form non-canonical, partially helical, stable folded structures with a small 1.4- to 1.7-nm radius of gyration, low count of three to six base pairs and six to nine base stacks, characterized by -34 to -51 kcal/mol free energy, -57 to -103 kcal/mol enthalpy, and -23 to -53 kcal/mol entropy for folding. The 4.5- to 6.2-cm3/g intrinsic viscosity and Huggins constant of 4.5-9.9 are indicative of extended and aggregating systems. The results obtained highlight the importance of the conformational ensemble view of PMO solution structures, thermodynamic stability of their non-canonical structures, and concentration-dependent viscosity properties. These principles form a paradigm to understand the structure-properties-function relationship for therapeutic PMOs to advance the design of new RNA-mimic-based drugs.

Interrelated effects of chromosome size, mechanics, number, location-orientation and polar ejection force on the spindle accuracy: a 3D computational study.

The search-and-capture model of spindle assembly has been a guiding principle for understanding prometaphase for decades. The computational model presented allows one to address two questions: how rapidly the microtubule-kinetochore connections are made, and how accurate these connections are. In most previous numerical simulations, the model geometry was drastically simplified. Using the CellDynaMo computational platform, we previously introduced a geometrically and mechanically realistic 3D model of the prometaphase mitotic spindle, and used it to evaluate thermal noise and microtubule kinetics effects on the capture of a single chromosome. Here, we systematically investigate how geometry and mechanics affect a spindle assembly's speed and accuracy, including nuanced distinctions between merotelic, mero-amphitelic, and mero-syntelic chromosomes. We find that softening of the centromere spring improves accuracy for short chromosome arms, but accuracy disappears for long chromosome arms. Initial proximity of chromosomes to one spindle pole makes assembly accuracy worse, while initial chromosome orientation matters less. Chromokinesins, added onto flexible chromosome arms, allow modeling of the polar ejection force, improving a spindle assembly's accuracy for a single chromosome. However, spindle space crowding by multiple chromosomes worsens assembly accuracy. Our simulations suggest that the complex microtubule network of the early spindle is key to rapid and accurate assembly.

CellDynaMo-stochastic reaction-diffusion-dynamics model: Application to search-and-capture process of mitotic spindle assembly.

We introduce a Stochastic Reaction-Diffusion-Dynamics Model (SRDDM) for simulations of cellular mechanochemical processes with high spatial and temporal resolution. The SRDDM is mapped into the CellDynaMo package, which couples the spatially inhomogeneous reaction-diffusion master equation to account for biochemical reactions and molecular transport within the Langevin Dynamics (LD) framework to describe dynamic mechanical processes. This computational infrastructure allows the simulation of hours of molecular machine dynamics in reasonable wall-clock time. We apply SRDDM to test performance of the Search-and-Capture of mitotic spindle assembly by simulating, in three spatial dimensions, dynamic instability of elastic microtubules anchored in two centrosomes, movement and deformations of geometrically realistic centromeres with flexible kinetochores and chromosome arms. Furthermore, the SRDDM describes the mechanics and kinetics of Ndc80 linkers mediating transient attachments of microtubules to the chromosomal kinetochores. The rates of these attachments and detachments depend upon phosphorylation states of the Ndc80 linkers, which are regulated in the model by explicitly accounting for the reactions of Aurora A and B kinase enzymes undergoing restricted diffusion. We find that there is an optimal rate of microtubule-kinetochore detachments which maximizes the accuracy of the chromosome connections, that adding chromosome arms to kinetochores improve the accuracy by slowing down chromosome movements, that Aurora A and kinetochore deformations have a small positive effect on the attachment accuracy, and that thermal fluctuations of the microtubules increase the rates of kinetochore capture and also improve the accuracy of spindle assembly.

Microtubule assembly and disassembly dynamics model: Exploring dynamic instability and identifying features of Microtubules' Growth, Catastrophe, Shortening, and Rescue.

Microtubules (MTs), a cellular structure element, exhibit dynamic instability and can switch stochastically from growth to shortening; but the factors that trigger these processes at the molecular level are not understood. We developed a 3D Microtubule Assembly and Disassembly DYnamics (MADDY) model, based upon a bead-per-monomer representation of the αß-tubulin dimers forming an MT lattice, stabilized by the lateral and longitudinal interactions between tubulin subunits. The model was parameterized against the experimental rates of MT growth and shortening, and pushing forces on the Dam1 protein complex due to protofilaments splaying out. Using the MADDY model, we carried out GPU-accelerated Langevin simulations to access dynamic instability behavior. By applying Machine Learning techniques, we identified the MT characteristics that distinguish simultaneously all four kinetic states: growth, catastrophe, shortening, and rescue. At the cellular 25 µM tubulin concentration, the most important quantities are the MT length L , average longitudinal curvature κ long , MT tip width w , total energy of longitudinal interactions in MT lattice U long , and the energies of longitudinal and lateral interactions required to complete MT to full cylinder U long add and U lat add . At high 250 µM tubulin concentration, the most important characteristics are L , κ long , number of hydrolyzed αß-tubulin dimers n hyd and number of lateral interactions per helical pitch n lat in MT lattice, energy of lateral interactions in MT lattice U lat , and energy of longitudinal interactions in MT tip u long . These results allow greater insights into what brings about kinetic state stability and the transitions between states involved in MT dynamic instability behavior.

Single-molecule conductance of double-stranded RNA oligonucleotides.

RNA oligonucleotides are crucial for a range of biological functions and in many biotechnological applications. Herein, we measured, for the first time, the conductance of individual double-stranded (ds)RNA molecules and compared it with the conductance of single DNA : RNA hybrids. The average conductance values are similar for both biomolecules, but the distribution of conductance values shows an order of magnitude higher variability for dsRNA, indicating higher molecular flexibility of dsRNA. Microsecond Molecular Dynamics simulations explain this difference and provide structural insights into the higher stability of DNA : RNA duplex with atomic level of detail. The rotations of 2'-OH groups of the ribose rings and the bases in RNA strands destabilize the duplex structure by weakening base stacking interactions, affecting charge transport, and making single-molecule conductance of dsRNA more variable (dynamic disorder). The results demonstrate that a powerful combination of state-of-the-art biomolecular electronics techniques and computational approaches can provide valuable insights into biomolecules' biophysics with unprecedented spatial resolution.