Adsorption of DNA Fragments at Aqueous Graphite and Au(111) via Integration of Experiment and Simulation.

We combine single molecule force spectroscopy measurements with all-atom metadynamics simulations to investigate the cross-materials binding strength trends of DNA fragments adsorbed at the aqueous graphite C(0001) and Au(111) interfaces. Our simulations predict this adsorption at the level of the nucleobase, nucleoside, and nucleotide. We find that despite challenges in making clear, careful connections between the experimental and simulation data, reasonable consistency between the binding trends between the two approaches and two substrates was evident. On C(0001), our simulations predict a binding trend of dG > dA ≈ dT > dC, which broadly aligns with the experimental trend. On Au(111), the simulation-based binding strength trends reveal stronger adsorption for the purines relative to the pyrimadines, with dG ≈ dA > dT ≈ dC. Moreover, our simulations provide structural insights into the origins of the similarities and differences in adsorption of the nucleic acid fragments at the two interfaces. In particular, our simulation data offer an explanation for the differences observed in the relative binding trend between adenosine and guanine on the two substrates.

Plasmon-enhanced two-photon-induced isomerization for highly-localized light-based actuation of inorganic/organic interfaces.

Two-photon initiated photo-isomerization of an azobenzene moiety adsorbed on silver nanoparticles (Ag NPs) is demonstrated. The azobenzene is linked to a materials-binding peptide that brings it into intimate contact with the Ag NP surface, producing a dramatic enhancement of its two-photon absorbance. An integrated modeling approach, combining advanced conformational sampling with Quantum Mechanics/Capacitance Molecular Mechanics and response theory, shows that charge transfer and image charges in the Ag NP generate local fields that enhance two-photon absorption of the cis isomer, but not the trans isomer, of adsorbed molecules. Moreover, dramatic local field enhancement is expected near the localized surface plasmon resonance (LSPR) wavelength, and the LSPR band of the Ag NPs overlaps the azobenzene absorbance that triggers cis to trans switching. As a result, the Ag NPs enable two-photon initiated cis to trans isomerization, but not trans to cis isomerization. Confocal anti-Stokes fluorescence imaging shows that this effect is not due to local heating, while the quadratic dependence of switching rate on laser intensity is consistent with a two-photon process. Highly localized two-photon initiated switching could allow local manipulation near the focal point of a laser within a 3D nanoparticle assembly, which cannot be achieved using linear optical processes.

Optical Actuation of Inorganic/Organic Interfaces: Comparing Peptide-Azobenzene Ligand Reconfiguration on Gold and Silver Nanoparticles.

Photoresponsive molecules that incorporate peptides capable of material-specific recognition provide a basis for biomolecule-mediated control of the nucleation, growth, organization, and activation of hybrid inorganic/organic nanostructures. These hybrid molecules interact with the inorganic surface through multiple noncovalent interactions which allow reconfiguration in response to optical stimuli. Here, we quantify the binding of azobenzene-peptide conjugates that exhibit optically triggered cis-trans isomerization on Ag surfaces and compare to their behavior on Au. These results demonstrate differences in binding and switching behavior between the Au and Ag surfaces. These molecules can also produce and stabilize Au and Ag nanoparticles in aqueous media where the biointerface can be reproducibly and reversibly switched by optically triggered azobenzene isomerization. Comparisons of switching rates and reversibility on the nanoparticles reveal differences that depend upon whether the azobenzene is attached at the peptide N- or C-terminus, its isomerization state, and the nanoparticle composition. Our integrated experimental and computational investigation shows that the number of ligand anchor sites strongly influences the nanoparticle size. As predicted by our molecular simulations, weaker contact between the hybrid biomolecules and the Ag surface, with fewer anchor residues compared with Au, gives rise to differences in switching kinetics on Ag versus Au. Our findings provide a pathway toward achieving new remotely actuatable nanomaterials for multiple applications from a single system, which remains difficult to achieve using conventional approaches.

Triggering nanoparticle surface ligand rearrangement via external stimuli: light-based actuation of biointerfaces.

Bio-molecular non-covalent interactions provide a powerful platform for material-specific self-organization in aqueous media. Here, we introduce a strategy that integrates a synthetic optically-responsive motif with a materials-binding peptide to enable remote actuation. Specifically, we linked a photoswitchable azobenzene moiety to either terminus of a Au-binding peptide. We employed these hybrid molecules as capping agents for synthesis of Au nanoparticles. Integrated experiments and molecular simulations showed that the hybrid molecules maintained both of their functions, i.e. binding to Au and optically-triggered reconfiguration. The azobenzene unit was optically switched reversibly between trans and cis states while adsorbed on the particle surface. Upon switching, the conformation of the peptide component of the molecule also changed. This highlights the interplay between the surface adsorption and conformational switching that will be pivotal to the creation of actuatable nanoparticle bio-interfaces, and paves the way toward multifunctional peptide hybrids that can produce stimuli responsive nanoassemblies.

The impact of carbon-hydrogen bond dissociation energies on the prediction of the cytochrome P450 mediated major metabolic site of drug-like compounds.

Cytochrome P450 is a family of enzymes which is estimated to be responsible for over 75% of phase I drug metabolism. In this process carbon hydrogen bonds (C-H) are broken for hydroxylation indicating that the bond dissociation energy (BDE) plays a pivotal role. A host of experimentally derived C-H BDEs were benchmarked against their theoretical counterparts and an excellent correlation was found (R(2) = 0.9746, n = 100). The C-H BDEs were calculated for fifty drugs with known major hydrogen abstraction sites. Of those twelve (24%) had their major metabolic site at the lowest C-H BDE. The most prominent factor in determining the metabolic site is the presence of tertiary and secondary amine moieties (44%). Other features such as lipophilicity and steric accessibility of the pertinent molecular scaffolds are also important. Nevertheless, out of the 586 C-H BDEs calculated the average of the major hydrogen abstraction sites are statistically significantly lower by 6.9-12.8 kcal/mol (p-value = 7.257 × 10(-9)). This means that C-H BDEs are an indispensable component in building reliable models of first pass metabolism of xenobiotics.

Size estimation of chemical space: how big is it?

OBJECTIVES: To estimate the size of organic chemical space and its sub-regions, i.e. drug-like chemical space and known drug space (KDS). METHODS: Analysis of the growth of organic compounds as a function of their carbon atoms based on a power function (f(x)=A×B, C=x) and an exponential function (f(x)=AeBx). Also, the statistical distribution of KDS and drug-like chemical space (drugs with good oral-bioavailability) based on their carbon atom count was used to deduce their size. KEY FINDINGS: The power function (f(x)=A×B, C=x) gives a superior fit to the growth of organic compounds leading to an estimate of 3.4×109 populating chemical space. KDS is predicted to be 2.0×106 molecules and drug-like chemical space is calculated to be 1.1×106 compounds. CONCLUSIONS: The values here are much smaller than previously reported. However, the numbers are large but not astronomical. A clear rationale on how we reach these numbers is given, which hopefully will lead to more refined predictions.