Poly(N-isopropylacrylamide) with hydrolyzable lactic acid ester side groups: a new type of thermosensitive polymer

N-isopropylacrylamide (NIPAAm) was copolymerized with 2-hydroxyethyl methacrylate-monolactate (HEMA-monolactate). With increasing HEMA-monolactate content in the copolymer, the lower critical solution temperature (LCST) decreases. During incubation in an aqueous solution, the lactate groups are released by hydrolysis, by which the copolymer is converted into poly(NIPAAm-co-HEMA). By this process, the hydrophilicity of the copolymer increases, resulting in increased LCST values.     

13C NMR Study of the grafting of 13C labeled maleic anhydride onto PE,PP and EPM

The chemical structure of polyolefins grafted with maleic anhydride (MA) has been the subject of much speculation, but thorough experimental studies are rare. MA with 99% ¹³C in the double bond was synthesized and grafted onto PE, EPM and PP in the melt and solution. 1D INADEQUATE ¹³C NMR spectroscopy was used to characterize the products. Saturated, monomeric MA graft structures are formed. Only for grafted PE short MA oligomers are demonstrated. Grafting occurs on secondary and tertiary carbons depending on the composition of the polyolefin. For PP a new, unsaturated MA graft structure on the polymer chain terminus is identified. All graft structures are rationalized using a simple grafting mechanism.     

On Epistemics in Expected Free Energy for Linear Gaussian State Space Models

Active Inference (AIF) is a framework that can be used both to describe information processing in naturally intelligent systems, such as the human brain, and to design synthetic intelligent systems (agents). In this paper we show that Expected Free Energy (EFE) minimisation, a core feature of the framework, does not lead to purposeful explorative behaviour in linear Gaussian dynamical systems. We provide a simple proof that, due to the specific construction used for the EFE, the terms responsible for the exploratory (epistemic) drive become constant in the case of linear Gaussian systems. This renders AIF equivalent to KL control. From a theoretical point of view this is an interesting result since it is generally assumed that EFE minimisation will always introduce an exploratory drive in AIF agents. While the full EFE objective does not lead to exploration in linear Gaussian dynamical systems, the principles of its construction can still be used to design objectives that include an epistemic drive. We provide an in-depth analysis of the mechanics behind the epistemic drive of AIF agents and show how to design objectives for linear Gaussian dynamical systems that do include an epistemic drive. Concretely, we show that focusing solely on epistemics and dispensing with goal-directed terms leads to a form of maximum entropy exploration that is heavily dependent on the type of control signals driving the system. Additive controls do not permit such exploration. From a practical point of view this is an important result since linear Gaussian dynamical systems with additive controls are an extensively used model class, encompassing for instance Linear Quadratic Gaussian controllers. On the other hand, linear Gaussian dynamical systems driven by multiplicative controls such as switching transition matrices do permit an exploratory drive.     

Paving the way to conformationally unravel complex glycopeptide antibiotics by means of Raman optical activity

It is crucial for fundamental physical chemistry techniques to find their application in tackling real-world challenges. Hitherto, Raman optical activity (ROA) spectroscopy is one of the examples where a promising future within the pharmaceutical sector is foreseen, but has not yet been established. Namely, the technique is believed to be able to contribute in investigating the conformational behaviour of drug candidates. We, herein, strive towards the alignment of the ROA analysis outcome and the pharmaceutical expectations by proposing a fresh strategy that ensures a more complete, reliable, and transferable ROA study. The strategy consists of the treatment of the conformational space by means of a principal component analysis (PCA) and a clustering algorithm, succeeded by a thorough ROA spectral analysis and a novel way of estimating the contributions of the different chemical fragments to the total ROA spectral intensities. Here, vancomycin, an antibiotic glycopeptide, has been treated; it is the first antibiotic glycopeptide studied by means of ROA and is a challenging compound in ROA terms. By applying our approach we discover that ROA is capable of independently identifying the correct conformation of vancomycin in aqueous solution. In addition, we have a clear idea of what ROA can and cannot tell us regarding glycopeptides. Finally, the glycopeptide class turns out to be a spectroscopically curious case, as its spectral responses are unlike the typical ROA spectral responses of peptides and carbohydrates. This preludes future ROA studies of this intriguing molecular class.

Raman optical activity tackles the complex conformational space of glycopeptide antibiotics.     

Don’t Overweight Weights: Evaluation of Weighting Strategies for Multi-Task Bioactivity Classification Models

Machine learning models predicting the bioactivity of chemical compounds belong nowadays to the standard tools of cheminformaticians and computational medicinal chemists. Multi-task and federated learning are promising machine learning approaches that allow privacy-preserving usage of large amounts of data from diverse sources, which is crucial for achieving good generalization and high-performance results. Using large, real world data sets from six pharmaceutical companies, here we investigate different strategies for averaging weighted task loss functions to train multi-task bioactivity classification models. The weighting strategies shall be suitable for federated learning and ensure that learning efforts are well distributed even if data are diverse. Comparing several approaches using weights that depend on the number of sub-tasks per assay, task size, and class balance, respectively, we find that a simple sub-task weighting approach leads to robust model performance for all investigated data sets and is especially suited for federated learning.     

Determination of interaction strength between corrole and phenol derivatives in aqueous media using atomic force microscopy

Atomic force microscopy (AFM) was used to measure single interaction forces between corrole (host) and phenol derivatives (guests) in aqueous media. A gold tip was modified with thiol derivatives of corrole via the Au–S covalent bond. Such a tip was used to measure adhesion forces with a planar gold substrate modified with thiol derivatives of phenol and ortho-nitrophenol in aqueous solutions. The mean force between the corrole and ortho-nitrophenol was higher than that between corrole and phenol, probably reflecting stronger hydrogen bond interaction in the former complex. In the presence of a supporting electrolyte (0.1 M K₂SO₄), the mean force increased, suggesting that electrostatic and π–π interactions play an essential role in the adhesion force. In addition, the adhesion force measured at pH 6.0 was larger than that at pH 10, reflecting the electrostatic repulsion at the higher pH. These behaviours are consistent with the potentiometric responses of a liquid membrane based on corrole to phenolic compounds. Also, the values of forces for the interaction between corrole and phenol derivatives showed the same tendency as energy calculated for these complexes. The Poisson method was used for the calculation of the single force of the chemical bond between the corrole host and the phenolic guests.     

Synthetic protocols towards homodithiacalix[n]arenes

Synthetic procedures towards homodithiacalix[n]arenes are developed, starting from simple and readily available bifunctional aryl building blocks, by a dynamic covalent chemistry approach. Reaction of 1,3-bis(mercaptomethyl)-5-tert-butyl-2-methoxybenzene under basic conditions leads to a mixture of trimeric, tetrameric and pentameric dimethylenedithia-bridged cyclooligomers, whereas reaction of 5-tert-butyl-2-methoxy-1,3-bis(thiocyanatomethyl) benzene under reducing conditions (and subsequent oxidation) affords the homodithiacalix[4]arene macrocycle in a very selective fashion through efficient disulphide exchange chemistry.     

Neutral Nickel Ethylene Oligo‐ and Polymerization Catalysts: Towards Computational Catalyst Prediction and Design

DFT calculations have been used to elucidate the chain termination mechanisms for neutral nickel ethylene oligo‐ and polymerization catalysts and to rationalize the kind of oligomers and polymers produced by each catalyst. The catalysts studied are the (κ²‐O,O)‐coordinated (1,1,1,5,5,5‐hexafluoro‐2,4‐acetylacetonato)nickel catalyst I , the (κ²‐P,O)‐coordinated SHOP‐type nickel catalyst II , the (κ²‐N,O)‐coordinated anilinotropone and salicylaldiminato nickel catalysts III and IV , respectively, and the (κ²‐P,N)‐coordinated phosphinosulfonamide nickel catalyst V . Numerous termination pathways involving β‐H elimination and β‐H transfer steps have been investigated, and the most probable routes identified. Despite the complexity and multitude of the possible termination pathways, the information most critical to chain termination is contained in only few transition states. In addition, by consideration of the propagation pathway, we have been able to estimate chain lengths and discriminate between oligo‐ and polymerization catalysts. In agreement with experiment, we found the Gibbs free energy difference between the overall barrier for the most facile propagation and termination pathways to be close to 0 kcal mol^?1 for the ethylene oligomerization catalysts I and V , whereas values of at least 7 kcal mol^?1 in favor of propagation were determined for the polymerization catalysts III and IV . Because of the shared intermediates between the termination and branching pathways, we have been able to identify the preferred cis/trans regiochemistry of β‐H elimination and show that a pronounced difference in σ donation of the two bridgehead atoms of the bidentate ligand can suppress hydride formation and thus branching. The degree of rationalization obtained here from a handful of key intermediates and transition states is promising for the use of computational methods in the screening and prediction of new catalysts of the title class.     

The first transition metal iodato peroxido complex: the synthesis, vibrational spectra and crystal structure from powder diffraction data of K3[V2O2(O2)4(IO3)]·H2O

The first transition metal iodato peroxido complex, K₃[V₂O₂(O₂)₄(IO₃)]·H₂O (I), was prepared by crystallization from the KVO₃ — KIO₃ — H₂O₂ — H₂O — ethanol (HNO₃) solution. The dinuclear anion is immediately decomposed in aqueous solution; the ⁵¹V NMR spectrum exhibits signals corresponding to [VO(O₂)₂(H₂O)]^?, [V₂O₂(OH)(O₂)₄]^3? and H₂VO₄ ^? species only. The IR and Raman spectra contain all characteristic bands of the VO(O₂)₂ group and the coordinated IO₃ ^? ligand. Based on the positions of bands assigned to the vibrations of the VO(O₂)₂ groups a pentagonal pyramidal arrangement around the vanadium atoms can be supposed. The crystal structure was solved from X-ray synchrotron powder data by direct space method and refined by energy minimization in the solid state employing a hybrid PBE0 functional. This crystal and molecular structure, has confirmed the presence of hexacoordinated vanadium atoms and revealed asymmetric dinuclear structure of the [V₂O₂(O₂)₄(IO₃)]^3? ion. The coordination spheres of vanadium atoms are different — the IO₃ ^? anion is coordinated only to one vanadium center. A thermal analysis of the complex confirmed the presence of water molecules in the crystal structure and revealed a considerable stability of the dehydrated complex.