Effect of Single-Residue Mutations on CTCF Binding to DNA: Insights from Molecular Dynamics Simulations.

In humans and other eukaryotes, DNA is condensed into chromatin fibers that are further wound into chromosomes. This organization allows regulatory elements in the genome, often distant from each other in the linear DNA, to interact and facilitate gene expression through regions known as topologically associating domains (TADs). CCCTC-binding factor (CTCF) is one of the major components of TAD formation and is responsible for recruiting a partner protein, cohesin, to perform loop extrusion and facilitate proper gene expression within TADs. Because single-residue CTCF mutations have been linked to the development of a variety of cancers in humans, we aim to better understand how these mutations affect the CTCF structure and its interaction with DNA. To this end, we compare all-atom molecular dynamics simulations of a wildtype CTCF-DNA complex to those of eight different cancer-linked CTCF mutant sequences. We find that most mutants have lower binding energies compared to the wildtype protein, leading to the formation of less stable complexes. Depending on the type and position of the mutation, this loss of stability can be attributed to major changes in the electrostatic potential, loss of hydrogen bonds between the CTCF and DNA, and/or destabilization of specific zinc fingers. Interestingly, certain mutations in specific fingers can affect the interaction with the DNA of other fingers, explaining why mere single mutations can impair CTCF function. Overall, these results shed mechanistic insights into experimental observations and further underscore CTCF's importance in the regulation of chromatin architecture and gene expression.

Obesogenic high-fat diet heightens aerobic glycolysis through hyperactivation of oncogenic KRAS.

Oncogenic KRAS plays a vital role in controlling tumor metabolism by enhancing aerobic glycolysis. Obesity driven by chronic consumption of high-fat diet (HFD) is a major risk factor for oncogenic KRAS-mediated pancreatic ductal adenocarcinoma (PDAC). However, the role of HFD in KRAS-mediated metabolic reprogramming has been obscure. Here, by using genetically engineered mouse models expressing an endogenous level of KRASG12D in pancreatic acinar cells, we demonstrate that hyperactivation of KRASG12D by obesogenic HFD, as compared to carbohydrate-rich diet, is responsible for enhanced aerobic glycolysis that associates with critical pathogenic responses in the path towards PDAC. Ablation of Cox-2 attenuates KRAS hyperactivation leading to the reversal of both aggravated aerobic glycolysis and high-grade dysplasia under HFD challenge. Our data highlight a pivotal role of the cooperative interaction between obesity-ensuing HFD and oncogenic KRAS in driving the heightened aerobic glycolysis during pancreatic tumorigenesis and suggest that in addition to directly targeting KRAS and aerobic glycolysis pathway, strategies to target the upstream of KRAS hyperactivation may bear important therapeutic value.

Describing sequence-ensemble relationships for intrinsically disordered proteins.

Intrinsically disordered proteins participate in important protein-protein and protein-nucleic acid interactions and control cellular phenotypes through their prominence as dynamic organizers of transcriptional, post-transcriptional and signalling networks. These proteins challenge the tenets of the structure-function paradigm and their functional mechanisms remain a mystery given that they fail to fold autonomously into specific structures. Solving this mystery requires a first principles understanding of the quantitative relationships between information encoded in the sequences of disordered proteins and the ensemble of conformations they sample. Advances in quantifying sequence-ensemble relationships have been facilitated through a four-way synergy between bioinformatics, biophysical experiments, computer simulations and polymer physics theories. In the present review we evaluate these advances and the resultant insights that allow us to develop a concise quantitative framework for describing the sequence-ensemble relationships of intrinsically disordered proteins.

Crystal lattice properties fully determine short-range interaction parameters for alkali and halide ions.

Accurate models of alkali and halide ions in aqueous solution are necessary for computer simulations of a broad variety of systems. Previous efforts to develop ion force fields have generally focused on reproducing experimental measurements of aqueous solution properties such as hydration free energies and ion-water distribution functions. This dependency limits transferability of the resulting parameters because of the variety and known limitations of water models. We present a solvent-independent approach to calibrating ion parameters based exclusively on crystal lattice properties. Our procedure relies on minimization of lattice sums to calculate lattice energies and interionic distances instead of equilibrium ensemble simulations of dense fluids. The gain in computational efficiency enables simultaneous optimization of all parameters for Li+, Na+, K+, Rb+, Cs+, F-, Cl-, Br-, and I- subject to constraints that enforce consistency with periodic table trends. We demonstrate the method by presenting lattice-derived parameters for the primitive model and the Lennard-Jones model with Lorentz-Berthelot mixing rules. The resulting parameters successfully reproduce the lattice properties used to derive them and are free from the influence of any water model. To assess the transferability of the Lennard-Jones parameters to aqueous systems, we used them to estimate hydration free energies and found that the results were in quantitative agreement with experimentally measured values. These lattice-derived parameters are applicable in simulations where coupling of ion parameters to a particular solvent model is undesirable. The simplicity and low computational demands of the calibration procedure make it suitable for parametrization of crystallizable ions in a variety of force fields.

Unmasking functional motifs within disordered regions of proteins.

Eukaryotic proteins often possess long stretches that fail to adopt well-defined, three-dimensional structures. These intrinsically disordered regions are associated with cell signaling through the enrichment of hub proteins of networks and as targets for posttranslational modifications. Although disordered regions are readily identified because of their distinct sequence characteristics, it is difficult to predict the functions associated with these regions. This is because disordered regions often house short (two- to five-residue) linear motifs that mediate intermolecular interactions. Predicting their function requires the ability to identify the functionally relevant motifs. If one assumes that functional motifs are highly conserved as compared to background sequence contexts, then a suitable comparative genomics approach proves to be powerful in unmasking functional motifs that are part of disordered regions. This approach has successfully identified known functional motifs and predicted a set of new motifs that might yield important insights regarding previously unknown functionalities for disordered regions. Given knowledge of highly conserved motifs, one can assess whether the rapidly changing sequence contexts are actuators of the functionalities of short linear motifs within disordered regions. This should have important implications for engineering and targeting hub proteins in signaling networks.

Improved atomistic Monte Carlo simulations demonstrate that poly-L-proline adopts heterogeneous ensembles of conformations of semi-rigid segments interrupted by kinks.

Poly-L-proline (PLP) polymers are useful mimics of biologically relevant proline-rich sequences. Biophysical and computational studies of PLP polymers in aqueous solutions are challenging because of the diversity of length scales and the slow time scales for conformational conversions. We describe an atomistic simulation approach that combines an improved ABSINTH implicit solvation model, with conformational sampling based on standard and novel Metropolis Monte Carlo moves. Refinements to forcefield parameters were guided by published experimental data for proline-rich systems. We assessed the validity of our simulation results through quantitative comparisons to experimental data that were not used in refining the forcefield parameters. Our analysis shows that PLP polymers form heterogeneous ensembles of conformations characterized by semirigid, rod-like segments interrupted by kinks, which result from a combination of internal cis peptide bonds, flexible backbone ψ angles, and the coupling between ring puckering and backbone degrees of freedom.

Net charge per residue modulates conformational ensembles of intrinsically disordered proteins.

Intrinsically disordered proteins (IDPs) adopt heterogeneous ensembles of conformations under physiological conditions. Understanding the relationship between amino acid sequence and conformational ensembles of IDPs can help clarify the role of disorder in physiological function. Recent studies revealed that polar IDPs favor collapsed ensembles in water despite the absence of hydrophobic groups--a result that holds for polypeptide backbones as well. By studying highly charged polypeptides, a different archetype of IDPs, we assess how charge content modulates the intrinsic preference of polypeptide backbones for collapsed structures. We characterized conformational ensembles for a set of protamines in aqueous milieus using molecular simulations and fluorescence measurements. Protamines are arginine-rich IDPs involved in the condensation of chromatin during spermatogenesis. Simulations based on the ABSINTH implicit solvation model predict the existence of a globule-to-coil transition, with net charge per residue serving as the discriminating order parameter. The transition is supported by quantitative agreement between simulation and experiment. Local conformational preferences partially explain the observed trends of polymeric properties. Our results lead to the proposal of a schematic protein phase diagram that should enable prediction of polymeric attributes for IDP conformational ensembles using easily calculated physicochemical properties of amino acid sequences. Although sequence composition allows the prediction of polymeric properties, interresidue contact preferences of protamines with similar polymeric attributes suggest that certain details of conformational ensembles depend on the sequence. This provides a plausible mechanism for specificity in the functions of IDPs.

Role of backbone-solvent interactions in determining conformational equilibria of intrinsically disordered proteins.

Intrinsically disordered proteins (IDPs) are functional proteins that do not fold into well-defined three-dimensional structures under physiological conditions. IDP sequences have low hydrophobicity, and hence, recent experiments have focused on quantitative studies of conformational ensembles of archetypal IDP sequences such as polyglutamine and glycine-serine block copolypeptides. Results from these experiments show that, despite the absence of hydrophobic residues, polar IDPs prefer ensembles of collapsed structures in aqueous milieus. Do these preferences originate in interactions that are unique to polar sidechains? The current study addresses this issue by analyzing conformational equilibria for polyglycine and a glycine-serine block copolypeptide in two environments, namely, water and 8 M urea. Polyglycine, a poly secondary-amide, has no sidechains and is a useful model system for generic polypeptide backbones. Results based on large-scale molecular dynamics simulations show that polyglycine forms compact, albeit disordered, globules in water and swollen, disordered coils in 8 M urea. There is minimal overlap between conformational ensembles in the two environments. Analysis of order parameters derived from theories for flexible polymers show that water at ambient temperatures is a poor solvent for generic polypeptide backbones. Therefore, the experimentally observed preferences for polyglutamine and glycine-serine block copolypeptides must originate, at least partially, in polypeptide backbones. A preliminary analysis of the driving forces that lead to distinct conformational preferences for polyglycine in two different environments is presented. Implications for describing conformational ensembles of generic IDP sequences are also discussed.

Automated image acquisition and processing using a new generation of 4K x 4K CCD cameras for cryo electron microscopic studies of macromolecular assemblies.

We have previously reported the development of AutoEM, a software package for semi-automated acquisition of data from a transmission electron microscope. In continuing efforts to improve the speed of structure determination of macromolecular assemblies by electron microscopy, we report here on the performance of a new generation of 4 K CCD cameras for use in cryo electron microscopic applications. We demonstrate that at 120 kV, and at a nominal magnification of 67000 x, power spectra and signal-to-noise ratios for the new 4 K CCD camera are comparable to values obtained for film images scanned using a Zeiss scanner to resolutions as high as approximately 1/6.5A(-1). The specimen area imaged for each exposure on the 4 K CCD is about one-third of the area that can be recorded with a similar exposure on film. The CCD camera also serves the purpose of recording images at low magnification from the center of the hole to measure the thickness of vitrified ice in the hole. The performance of the camera is satisfactory under the low-dose conditions used in cryo electron microscopy, as demonstrated here by the determination of a three-dimensional map at 15 A for the catalytic core of the 1.8 MDa Bacillus stearothermophilus icosahedral pyruvate dehydrogenase complex, and its comparison with the previously reported atomic model for this complex obtained by X-ray crystallography.