Residue coevolution and mutational landscape for OmpR and NarL response regulator subfamilies.

DNA-binding response regulators (DBRRs) are a broad class of proteins that operate in tandem with their partner kinase proteins to form two-component signal transduction systems in bacteria. Typical DBRRs are composed of two domains where the conserved N-terminal domain accepts transduced signals and the evolutionarily diverse C-terminal domain binds to DNA. These domains are assumed to be functionally independent, and hence recombination of the two domains should yield novel DBRRs of arbitrary input/output response, which can be used as biosensors.

Structural reorganization and relaxation dynamics of axially stressed chromosomes.

Chromosomes endure mechanical stresses throughout the cell cycle; for example, resulting from the pulling of chromosomes by spindle fibers during mitosis or deformation of the nucleus during cell migration. The response to physical stress is closely related to chromosome structure and function. Micromechanical studies of mitotic chromosomes have revealed them to be remarkably extensible objects and informed early models of mitotic chromosome organization.

Exploring chromosomal structural heterogeneity across multiple cell lines.

Using computer simulations, we generate cell-specific 3D chromosomal structures and compare them to recently published chromatin structures obtained through microscopy. We demonstrate using machine learning and polymer physics simulations that epigenetic information can be used to predict the structural ensembles of multiple human cell lines. Theory predicts that chromosome structures are fluid and can only be described by an ensemble, which is consistent with the observation that chromosomes exhibit no unique fold.

The Nucleome Data Bank: web-based resources to simulate and analyze the three-dimensional genome.

We introduce the Nucleome Data Bank (NDB), a web-based platform to simulate and analyze the three-dimensional (3D) organization of genomes. The NDB enables physics-based simulation of chromosomal structural dynamics through the MEGABASE + MiChroM computational pipeline. The input of the pipeline consists of epigenetic information sourced from the Encode database; the output consists of the trajectories of chromosomal motions that accurately predict Hi-C and fluorescence insitu hybridization data, as well as multiple observations of chromosomal dynamics in vivo.

Structure-Based Model of RNA Pseudoknot Captures Magnesium-Dependent Folding Thermodynamics.

We develop a simple, coarse-grained approach for simulating the folding of the Beet Western Yellow Virus (BWYV) pseudoknot toward the goal of creating a transferable model that can be used to study other small RNA molecules. This approach combines a structure-based model (SBM) of RNA with an electrostatic scheme that has previously been shown to correctly reproduce ionic condensation in the native basin. Mg ions are represented explicitly, directly incorporating ion-ion correlations into the system, and K is represented implicitly, through the mean-field generalized Manning counterion condensation theory.

Designing bacterial signaling interactions with coevolutionary landscapes.

Selecting amino acids to design novel protein-protein interactions that facilitate catalysis is a daunting challenge. We propose that a computational coevolutionary landscape based on sequence analysis alone offers a major advantage over expensive, time-consuming brute-force approaches currently employed. Our coevolutionary landscape allows prediction of single amino acid substitutions that produce functional interactions between non-cognate, interspecies signaling partners.

The Energetics and Physiological Impact of Cohesin Extrusion.

Cohesin extrusion is thought to play a central role in establishing the architecture of mammalian genomes. However, extrusion has not been visualized in vivo, and thus, its functional impact and energetics are unknown. Using ultra-deep Hi-C, we show that loop domains form by a process that requires cohesin ATPases.

Elucidating the druggable interface of protein-protein interactions using fragment docking and coevolutionary analysis.

Protein-protein interactions play a central role in cellular function. Improving the understanding of complex formation has many practical applications, including the rational design of new therapeutic agents and the mechanisms governing signal transduction networks. The generally large, flat, and relatively featureless binding sites of protein complexes pose many challenges for drug design.

Constructing sequence-dependent protein models using coevolutionary information.

Recent developments in global statistical methodologies have advanced the analysis of large collections of protein sequences for coevolutionary information. Coevolution between amino acids in a protein arises from compensatory mutations that are needed to maintain the stability or function of a protein over the course of evolution. This gives rise to quantifiable correlations between amino acid sites within the multiple sequence alignment of a protein family.

Coevolutionary information, protein folding landscapes, and the thermodynamics of natural selection.

The energy landscape used by nature over evolutionary timescales to select protein sequences is essentially the same as the one that folds these sequences into functioning proteins, sometimes in microseconds. We show that genomic data, physical coarse-grained free energy functions, and family-specific information theoretic models can be combined to give consistent estimates of energy landscape characteristics of natural proteins. One such characteristic is the effective temperature T(sel) at which these foldable sequences have been selected in sequence space by evolution.

Toward rationally redesigning bacterial two-component signaling systems using coevolutionary information.

A challenge in molecular biology is to distinguish the key subset of residues that allow two-component signaling (TCS) proteins to recognize their correct signaling partner such that they can transiently bind and transfer signal, i.e., phosphoryl group.

Exploring the role of internal friction in the dynamics of unfolded proteins using simple polymer models.

Recent experiments showed that the reconfiguration dynamics of unfolded proteins are often adequately described by simple polymer models. In particular, the Rouse model with internal friction (RIF) captures internal friction effects as observed in single-molecule fluorescence correlation spectroscopy (FCS) studies of a number of proteins. Here we use RIF, and its non-free draining analog, Zimm model with internal friction, to explore the effect of internal friction on the rate with which intramolecular contacts can be formed within the unfolded chain.

Quantifying internal friction in unfolded and intrinsically disordered proteins with single-molecule spectroscopy.

Internal friction, which reflects the "roughness" of the energy landscape, plays an important role for proteins by modulating the dynamics of their folding and other conformational changes. However, the experimental quantification of internal friction and its contribution to folding dynamics has remained challenging. Here we use the combination of single-molecule Förster resonance energy transfer, nanosecond fluorescence correlation spectroscopy, and microfluidic mixing to determine the reconfiguration times of unfolded proteins and investigate the mechanisms of internal friction contributing to their dynamics.

Charge-site-dependent dissociation of hydrogen-rich radical peptide cations upon vacuum UV photoexcitation.

Here, 193 nm vacuum ultraviolet photodissociation (VUVPD) was used to investigate the fragmentation of hydrogen-rich radical peptide cations generated by electron transfer reactions. VUVPD offers new insight into the factors that drive radical- and photon-directed processes. The location of a basic Arg site influences photon-activated C(α)-C(O) bond cleavages of singly charged peptide radical cations, an outcome attributed to the initial conformation of the peptide as supported by molecular dynamics simulated annealing and the population of excited states upon UV excitation.

Universality in the timescales of internal loop formation in unfolded proteins and single-stranded oligonucleotides.

Understanding the rate at which various parts of a molecular chain come together to facilitate the folding of a biopolymer (e.g., a protein or RNA) into its functional form remains an elusive goal.

A mechanistic study of electron transfer from the distal termini of electrode-bound, single-stranded DNAs.

Electrode-bound, redox-reporter-modified oligonucleotides play roles in the functioning of a number of electrochemical biosensors, and thus the question of electron transfer through or from such molecules has proven of significant interest. In response, we have experimentally characterized the rate with which electrons are transferred between a methylene blue moiety on the distal end of a short, single-stranded polythymine DNA to a monolayer-coated gold electrode to which the other end of the DNA is site-specifically attached. We find that this rate scales with oligonucleotide length to the -1.

End-to-surface reaction dynamics of a single surface-attached DNA or polypeptide.

The dynamics of surface-attached polymers play a key role in the operation of a number of biological sensors, yet its current understanding is rather limited. Here we use computer simulations to study the dynamics of a reaction between the free end of a polymer chain and a surface, to which its other end has been attached. We consider two limiting cases, the diffusion-controlled limit, where the reaction is accomplished whenever the free chain end diffuses to within a specified distance from the surface, and the reaction-controlled limit, where slow, intrinsic reaction kinetics rather than diffusion of the chain is rate limiting.