Michael D. Daily

Structure-Based Predictive Models for Allosteric Hot Spots

In allostery, a binding event at one site in a protein modulates the behavior of a distant site. Identifying residues that relay the signal between sites remains a challenge. We have developed predictive models using support-vector machines, a widely used machine-learning method. The training data set consisted of residues classified as either hotspots or non-hotspots based on experimental characterization of point mutations from a diverse set of allosteric proteins. Each residue had an associated set of calculated features. Two sets of features were used, one consisting of dynamical, structural, network, and informatic measures, and another of structural measures defined by Daily and Gray [1]. The resulting models performed well on an independent data set consisting of hotspots and non-hotspots from five allosteric proteins. For the independent data set, our top 10 models using Feature Set 1 recalled 68–81% of known hotspots, and among total hotspot predictions, 58–67% were actual hotspots. Hence, these models have precision P = 58–67% and recall R = 68–81%. The corresponding models for Feature Set 2 had P = 55–59% and R = 81–92%. We combined the features from each set that produced models with optimal predictive performance. The top 10 models using this hybrid feature set had R = 73–81% and P = 64–71%, the best overall performance of any of the sets of models. Our methods identified hotspots in structural regions of known allosteric significance. Moreover, our predicted hotspots form a network of contiguous residues in the interior of the structures, in agreement with previous work. In conclusion, we have developed models that discriminate between known allosteric hotspots and non-hotspots with high accuracy and sensitivity. Moreover, the pattern of predicted hotspots corresponds to known functional motifs implicated in allostery, and is consistent with previous work describing sparse networks of allosterically important residues.

Triazine-Based Sequence-Defined Polymers with Side-Chain Diversity and Backbone–Backbone Interaction Motifs

Abstract Sequence control in polymers, well‐known in nature, encodes structure and functionality. Here we introduce a new architecture, based on the nucleophilic aromatic substitution chemistry of cyanuric chloride, that creates a new class of sequence‐defined polymers dubbed TZPs. Proof of concept is demonstrated with two synthesized hexamers, having neutral and ionizable side chains. Molecular dynamics simulations show backbone–backbone interactions, including H‐bonding motifs and pi–pi interactions. This architecture is arguably biomimetic while differing from sequence‐defined polymers having peptide bonds. The synthetic methodology supports the structural diversity of side chains known in peptides, as well as backbone–backbone hydrogen‐bonding motifs, and will thus enable new macromolecules and materials with useful functions.

The Structural Basis of Cholesterol Accessibility in Membranes

Although the majority of free cellular cholesterol is present in the plasma membrane, cholesterol homeostasis is principally regulated through sterol-sensing proteins that reside in the cholesterol-poor endoplasmic reticulum (ER). In response to acute cholesterol loading or depletion, there is rapid equilibration between the ER and plasma membrane cholesterol pools, suggesting a biophysical model in which the availability of plasma membrane cholesterol for trafficking to internal membranes modulates ER membrane behavior. Previous studies have predominantly examined cholesterol availability in terms of binding to extramembrane acceptors, but have provided limited insight into the structural changes underlying cholesterol activation. In this study, we use both molecular dynamics simulations and experimental membrane systems to examine the behavior of cholesterol in membrane bilayers. We find that cholesterol depth within the bilayer provides a reasonable structural metric for cholesterol availability and that this is correlated with cholesterol-acceptor binding. Further, the distribution of cholesterol availability in our simulations is continuous rather than divided into distinct available and unavailable pools. This data provide support for a revised cholesterol activation model in which activation is driven not by saturation of membrane-cholesterol interactions but rather by bulk membrane remodeling that reduces membrane-cholesterol affinity.

Trimeric Structure of (+)-Pinoresinol-forming Dirigent Protein at 1.95 Å Resolution with Three Isolated Active Sites

Background: Dirigent protein (DP) discovery gave new paradigm for monolignol-derived coupling in planta. Results: (+)-Pinoresinol-forming DP (PsDRR206) three-dimensional structure was obtained at 1.95 Å resolution. Conclusion: The tightly packed trimeric DP has three putative substrate binding sites spatially far apart, suggesting that each site involves monomer coupling directly. Significance: New insights into monolignol radical-radical coupling in planta. Control over phenoxy radical-radical coupling reactions in vivo in vascular plants was enigmatic until our discovery of dirigent proteins (DPs, from the Latin dirigere, to guide or align). The first three-dimensional structure of a DP ((+)-pinoresinol-forming DP, 1.95 Å resolution, rhombohedral space group H32)) is reported herein. It has a tightly packed trimeric structure with an eight-stranded β-barrel topology for each DP monomer. Each putative substrate binding and orientation coupling site is located on the trimer surface but too far apart for intermolecular coupling between sites. It is proposed that each site enables stereoselective coupling (using either two coniferyl alcohol radicals or a radical and a monolignol). Interestingly, there are six differentially conserved residues in DPs affording either the (+)- or (−)-antipodes in the vicinity of the putative binding site and region known to control stereoselectivity. DPs are involved in lignan biosynthesis, whereas dirigent domains/sites have been implicated in lignin deposition.

Improved Coarse-Grained Modeling of Cholesterol-Containing Lipid Bilayers.

Cholesterol trafficking, which is an essential function in mammalian cells, is intimately connected to molecular-scale interactions through cholesterol modulation of membrane structure and dynamics and interaction with membrane receptors. Since these effects of cholesterol occur on micro- to millisecond time scales, it is essential to develop accurate coarse-grained simulation models that can reach these time scales. Cholesterol has been shown experimentally to thicken the membrane and increase phospholipid tail order between 0 and 40% cholesterol, above which these effects plateau or slightly decrease. Here, we showed that the published MARTINI coarse-grained force-field for phospholipid (POPC) and cholesterol fails to capture these effects. Using reference atomistic simulations, we systematically modified POPC and cholesterol bonded parameters in MARTINI to improve its performance. We showed that the corrections to pseudobond angles between glycerol and the lipid tails and around the oleoyl double bond particle (the “angle-corrected model”) slightly improves the agreement of MARTINI with experimentally measured thermal, elastic, and dynamic properties of POPC membranes. The angle-corrected model improves prediction of the thickening and ordering effects up to 40% cholesterol but overestimates these effects at higher cholesterol concentration. In accordance with prior work that showed the cholesterol rough face methyl groups are important for limiting cholesterol self-association, we revised the coarse-grained representation of these methyl groups to better match cholesterol-cholesterol radial distribution functions from atomistic simulations. In addition, by using a finer-grained representation of the branched cholesterol tail than MARTINI, we improved predictions of lipid tail order and bilayer thickness across a wide range of concentrations. Finally, transferability testing shows that a model incorporating our revised parameters into DOPC outperforms other CG models in a DOPC/cholesterol simulation series, which further argues for its efficacy and generalizability. These results argue for the importance of systematic optimization for coarse-graining biologically important molecules like cholesterol with complicated molecular structure.

Numerical calculation of protein-ligand binding rates through solution of the Smoluchowski equation using smoothed particle hydrodynamics

BackgroundThe calculation of diffusion-controlled ligand binding rates is important for understanding enzyme mechanisms as well as designing enzyme inhibitors.MethodsWe demonstrate the accuracy and effectiveness of a Lagrangian particle-based method, smoothed particle hydrodynamics (SPH), to study diffusion in biomolecular systems by numerically solving the time-dependent Smoluchowski equation for continuum diffusion. Unlike previous studies, a reactive Robin boundary condition (BC), rather than the absolute absorbing (Dirichlet) BC, is considered on the reactive boundaries. This new BC treatment allows for the analysis of enzymes with “imperfect” reaction rates.ResultsThe numerical method is first verified in simple systems and then applied to the calculation of ligand binding to a mouse acetylcholinesterase (mAChE) monomer. Rates for inhibitor binding to mAChE are calculated at various ionic strengths and compared with experiment and other numerical methods. We find that imposition of the Robin BC improves agreement between calculated and experimental reaction rates.ConclusionsAlthough this initial application focuses on a single monomer system, our new method provides a framework to explore broader applications of SPH in larger-scale biomolecular complexes by taking advantage of its Lagrangian particle-based nature.

Origin of parameter degeneracy and molecular shape relationships in geometric-flow calculations of solvation free energies

Implicit solvent models are important tools for calculating solvation free energies for chemical and biophysical studies since they require fewer computational resources but can achieve accuracy comparable to that of explicit-solvent models. In past papers, geometric flow-based solvation models have been established for solvation analysis of small and large compounds. In the present work, the use of realistic experiment-based parameter choices for the geometric flow models is studied. We find that the experimental parameters of solvent internal pressure p = 172 MPa and surface tension γ = 72 mN/m produce solvation free energies within 1 RT of the global minimum root-mean-squared deviation from experimental data over the expanded set. Our results demonstrate that experimental values can be used for geometric flow solvent model parameters, thus eliminating the need for additional parameterization. We also examine the correlations between optimal values of p and γ which are strongly anti-correlated. Geometric analysis of the small molecule test set shows that these results are inter-connected with an approximately linear relationship between area and volume in the range of molecular sizes spanned by the data set. In spite of this considerable degeneracy between the surface tension and pressure terms in the model, both terms are important for the broader applicability of the model.

Structural and functional characterization of DUF1471 domains of Salmonella proteins SrfN, YdgH/SssB, and YahO.

Bacterial species in the Enterobacteriaceae typically contain multiple paralogues of a small domain of unknown function (DUF1471) from a family of conserved proteins also known as YhcN or BhsA/McbA. Proteins containing DUF1471 may have a single or three copies of this domain. Representatives of this family have been demonstrated to play roles in several cellular processes including stress response, biofilm formation, and pathogenesis. We have conducted NMR and X-ray crystallographic studies of four DUF1471 domains from Salmonella representing three different paralogous DUF1471 subfamilies: SrfN, YahO, and SssB/YdgH (two of its three DUF1471 domains: the N-terminal domain I (residues 21–91), and the C-terminal domain III (residues 244–314)). Notably, SrfN has been shown to have a role in intracellular infection by Salmonella Typhimurium. These domains share less than 35% pairwise sequence identity. Structures of all four domains show a mixed α+β fold that is most similar to that of bacterial lipoprotein RcsF. However, all four DUF1471 sequences lack the redox sensitive cysteine residues essential for RcsF activity in a phospho-relay pathway, suggesting that DUF1471 domains perform a different function(s). SrfN forms a dimer in contrast to YahO and SssB domains I and III, which are monomers in solution. A putative binding site for oxyanions such as phosphate and sulfate was identified in SrfN, and an interaction between the SrfN dimer and sulfated polysaccharides was demonstrated, suggesting a direct role for this DUF1471 domain at the host-pathogen interface.