Root-aligned SMILES: a tight representation for chemical reaction prediction

Chemical reaction prediction, involving forward synthesis and retrosynthesis prediction, is a fundamental problem in organic synthesis. A popular computational paradigm formulates synthesis prediction as a sequence-to-sequence translation problem, where the typical SMILES is adopted for molecule representations. However, the general-purpose SMILES neglects the characteristics of chemical reactions, where the molecular graph topology is largely unaltered from reactants to products, resulting in the suboptimal performance of SMILES if straightforwardly applied. In this article, we propose the root-aligned SMILES (R-SMILES), which specifies a tightly aligned one-to-one mapping between the product and the reactant SMILES for more efficient synthesis prediction. Due to the strict one-to-one mapping and reduced edit distance, the computational model is largely relieved from learning the complex syntax and dedicated to learning the chemical knowledge for reactions. We compare the proposed R-SMILES with various state-of-the-art baselines and show that it significantly outperforms them all, demonstrating the superiority of the proposed method.

We propose the root-aligned SMILES (R-SMILES), which specifies a tightly aligned one-to-one mapping between the product and the reactant SMILES for more efficient sequence-based synthesis prediction.     

The development of a comprehensive toolbox based on multi-level,high-throughput screening of MOFs for CO/N2 separations

The separation of CO/N₂ mixtures is a challenging problem in the petrochemical sector due to the very similar physical properties of these two molecules, such as size, molecular weight and boiling point. To solve this and other challenging gas separations, one requires a holistic approach. The complexity of a screening exercise for adsorption-based separations arises from the multitude of existing porous materials, including metal–organic frameworks. Besides, the multivariate nature of the performance criteria that needs to be considered when designing an optimal adsorbent and a separation process – i.e. an optimal material requires fulfillment of several criteria simultaneously – makes the screening challenging. To address this, we have developed a multi-scale approach combining high-throughput molecular simulation screening, data mining and advanced visualization, as well as process system modelling, backed up by experimental validation. We have applied our recent advances in the engineering of porous materials'' morphology to develop advanced monolithic structures. These conformed, shaped monoliths can be used readily in industrial applications, bringing a valuable strategy for the development of advanced materials. This toolbox is flexible enough to be applied to multiple adsorption-based gas separation applications.

The separation of challenging mixtures through adsorption is a multidimensional problem that requires a holistic approach. Our toolbox combines experiments, molecular and process simulations with data visualization to find optimal, porous materials.     

Charge transport through extended molecular wires with strongly correlated electrons

Electron–electron interactions are at the heart of chemistry and understanding how to control them is crucial for the development of molecular-scale electronic devices. Here, we investigate single-electron tunneling through a redox-active edge-fused porphyrin trimer and demonstrate that its transport behavior is well described by the Hubbard dimer model, providing insights into the role of electron–electron interactions in charge transport. In particular, we empirically determine the molecule''s on-site and inter-site electron–electron repulsion energies, which are in good agreement with density functional calculations, and establish the molecular electronic structure within various oxidation states. The gate-dependent rectification behavior confirms the selection rules and state degeneracies deduced from the Hubbard model. We demonstrate that current flow through the molecule is governed by a non-trivial set of vibrationally coupled electronic transitions between various many-body ground and excited states, and experimentally confirm the importance of electron–electron interactions in single-molecule devices.

Experimental studies of electron transport through an edge-fused porphyrin oligomer in a graphene junction are interpreted within a Hubbard dimer framework.     

Coarse-grained modelling to predict the packing of porous organic cages

How molecules pack has vital ramifications for their applications as functional molecular materials. Small changes in a molecule''s functionality can lead to large, non-intuitive, changes in their global solid-state packing, resulting in difficulty in targeted design. Predicting the crystal structure of organic molecules from only their molecular structure is a well-known problem plaguing crystal engineering. Although relevant to the properties of many organic molecules, the packing behaviour of modular porous materials, such as porous organic cages (POCs), greatly impacts the properties of the material. We present a novel way of predicting the solid-state phase behaviour of POCs by using a simplistic model containing the dominant degrees of freedom driving crystalline phase formation. We employ coarse-grained simulations to systematically study how chemical functionality of pseudo-octahedral cages can be used to manipulate the solid-state phase formation of POCs. Our results support those of experimentally reported structures, showing that for cages which pack via their windows forming a porous network, only one phase is formed, whereas when cages pack via their windows and arenes, the phase behaviour is more complex. While presenting a lower computational cost route for predicting molecular crystal packing, coarse-grained models also allow for the development of design rules which we start to formulate through our results.

This work presents a novel method for predicting molecular crystal structure formation using coarse-grained modelling, enabling the development of design rules.     

Attention-based generative models for de novo molecular design

Attention mechanisms have led to many breakthroughs in sequential data modeling but have yet to be incorporated into any generative algorithms for molecular design. Here we explore the impact of adding self-attention layers to generative β-VAE models and show that those with attention are able to learn a complex “molecular grammar” while improving performance on downstream tasks such as accurately sampling from the latent space (“model memory”) or exploring novel chemistries not present in the training data. There is a notable relationship between a model''s architecture, the structure of its latent memory and its performance during inference. We demonstrate that there is an unavoidable tradeoff between model exploration and validity that is a function of the complexity of the latent memory. However, novel sampling schemes may be used that optimize this tradeoff. We anticipate that attention will play an important role in future molecular design algorithms that can make efficient use of the detailed molecular substructures learned by the transformer.

An implementation of attention within the variational autoencoder framework for continuous representation of molecules. The addition of attention significantly increases model performance for complex tasks such as exploration of novel chemistries.     

Recent progress and future challenges in the supramolecular polymerization of metal-containing monomers

The self-assembly of discrete molecular entities into functional nanomaterials has become a major research area in the past decades. The library of investigated compounds has diversified significantly, while the field as a whole has matured. The incorporation of metal ions in the molecular design of the (supra-)molecular building blocks greatly expands the potential applications, while also offering a promising approach to control molecular recognition and attractive and/or repulsive intermolecular binding events. Hence, supramolecular polymerization of metal-containing monomers has emerged as a major research focus in the field. In this perspective article, we highlight recent significant advances in supramolecular polymerization of metal-containing monomers and discuss their implications for future research. Additionally, we also outline some major challenges that metallosupramolecular chemists (will) have to face to produce metallosupramolecular polymers (MSPs) with advanced applications and functionalities.

In this perspective article, we highlight recent significant advances in the self-assembly of metal-containing monomers and discuss their implications for future research.     

Molecular planting of a single organothiol into a “gap-site” of a 2D patterned adlayer in an electrochemical environment

The self-assembled inclusion of molecules into two-dimensional (2D) porous networks on surfaces has been extensively studied because 2D functional materials consisting of organic molecules have become an important research topic. However, the isolation of a single molecular thiol remains a challenging goal. Here, we report a method of planting and isolating organothiols onto a 2D patterned organic adlayer at an electrochemical interface. In situ scanning tunneling microscopy revealed that the phase transition of an ovalene adlayer is electrochemically induced and that the gap site created by three ovalene molecules serves as a 2D molecular template to isolate thiol molecules and to standardize the distance between them via the formation of precise selective open spaces, suggesting that electrochemical “molecular planting” opens applications for 2D patterns of isolated single organothiol molecules.

Gap sites electrochemically created in the ovalene adlayer can accept a single thiol.     

Stereoselective β-mannosylations and β-rhamnosylations from glycosyl hemiacetals mediated by lithium iodide

Stereoselective β-mannosylation is one of the most challenging problems in the synthesis of oligosaccharides. Herein, a highly selective synthesis of β-mannosides and β-rhamnosides from glycosyl hemi-acetals is reported, following a one-pot chlorination, iodination, glycosylation sequence employing cheap oxalyl chloride, phosphine oxide and LiI. The present protocol works excellently with a wide range of glycosyl acceptors and with armed glycosyl donors. The method doesn''t require conformationally restricted donors or directing groups; it is proposed that the high β-selectivities observed are achieved via an S_N2-type reaction of α-glycosyl iodide promoted by lithium iodide.

Breaking from the current paradigm, a highly selective synthesis of hard-to-make β-mannosides and β-rhamnosides from simple glycosyl hemi-acetals has been achieved without using conformational restrictions.     

Dielectric response of thin water films: a thermodynamic perspective

The surface of a polar liquid presents a special environment for the solvation and organization of charged solutes, which differ from bulk behaviors in important ways. These differences have motivated many attempts to understand electrostatic response at aqueous interfaces in terms of a spatially varying dielectric permittivity, typically concluding that the dielectric constant of interfacial water is significantly lower than in the bulk liquid. Such analyses, however, are complicated by the potentially nonlocal nature of dielectric response over the short length scales of interfacial heterogeneity. Here we circumvent this problem for thin water films by adopting a thermodynamic approach. Using molecular simulations, we calculate the solvent''s contribution to the reversible work of charging a parallel plate capacitor. We find good agreement with a simple dielectric continuum model that assumes bulk dielectric permittivity all the way up to the liquid''s boundary, even for very thin (∼1 nm) films. This comparison requires careful attention to the placement of dielectric boundaries between liquid and vapor, which also resolves apparent discrepancies with dielectric imaging experiments.

Free energy calculations from molecular simulations reveal that water''s interfacial dielectric response is well-described by bulk properties.     

Photodriven water oxidation initiated by a surface bound chromophore-donor-catalyst assembly

In photosynthesis, solar energy is used to produce solar fuels in the form of new chemical bonds. A critical step to mimic photosystem II (PS II), a key protein in nature''s photosynthesis, for artificial photosynthesis is designing devices for efficient light-driven water oxidation. Here, we describe a single molecular assembly electrode that duplicates the key components of PSII. It consists of a polypyridyl light absorber, chemically linked to an intermediate electron donor, with a molecular-based water oxidation catalyst on a SnO₂/TiO₂ core/shell electrode. The synthetic device mimics PSII in achieving sustained, light-driven water oxidation catalysis. It highlights the value of the tyrosine–histidine pair in PSII in achieving efficient water oxidation catalysis in artificial photosynthetic devices.

We describe a single molecular assembly electrode that mimics PSII. Flash photolysis revealed the electron transfer steps between chromophore light absorption and the creation and storage of redox equivalents in the catalyst for water oxidation.     

Broadband measurement of true transverse relaxation rates in systems with coupled protons: application to the study of conformational exchange

Accurate measurement of transverse relaxation rates in coupled spin systems is important in the study of molecular dynamics, but is severely complicated by the signal modulations caused by scalar couplings in spin echo experiments. The most widely used experiments for measuring transverse relaxation in coupled systems, CPMG and PROJECT, can suppress such modulations, but they also both suppress some relaxation contributions, and average relaxation rates between coupled spins. Here we introduce a new experiment which for the first time allows accurate broadband measurement of transverse relaxation rates of coupled protons, and hence the determination of exchange rate constants in slow exchange from relaxation measurements. The problems encountered with existing methods are illustrated, and the use of the new method is demonstrated for the classic case of hindered amide rotation and for the more challenging problem of exchange between helical enantiomers of a gold(i) complex.

Existing methods for measuring transverse relaxation give incorrect results in coupled spin systems. Measuring true relaxation rates extends their utility.     

A novel chemical biology and computational approach to expedite the discovery of new-generation polymyxins against life-threatening Acinetobacter baumannii

Multidrug-resistant Gram-negative bacteria represent a major medical challenge worldwide. New antibiotics are desperately required with ‘old’ polymyxins often being the only available therapeutic option. Here, we systematically investigated the structure–activity relationship (SAR) of polymyxins using a quantitative lipidomics-informed outer membrane (OM) model of Acinetobacter baumannii and a series of chemically synthesized polymyxin analogs. By integrating chemical biology and all-atom molecular dynamics simulations, we deciphered how each residue of the polymyxin molecule modulated its conformational folding and specific interactions with the bacterial OM. Importantly, a novel designed polymyxin analog FADDI-287 with predicted stronger OM penetration showed improved in vitro antibacterial activity. Collectively, our study provides a novel chemical biology and computational strategy to expedite the discovery of new-generation polymyxins against life-threatening Gram-negative ‘superbugs’.

Multidrug-resistant Gram-negative bacteria have been an urgent threat to global public health. Novel antibiotics are desperately needed to combat these ''superbugs''.     

Structure-mechanics statistical learning uncovers mechanical relay in proteins

A protein''s adaptive response to its substrates is one of the key questions driving molecular physics and physical chemistry. This work employs the recently developed structure-mechanics statistical learning method to establish a mechanical perspective. Specifically, by mapping all-atom molecular dynamics simulations onto the spring parameters of a backbone-side-chain elastic network model, the chemical moiety specific force constants (or mechanical rigidity) are used to assemble the rigidity graph, which is the matrix of inter-residue coupling strength. Using the S1A protease and the PDZ3 signaling domain as examples, chains of spatially contiguous residues are found to exhibit prominent changes in their mechanical rigidity upon substrate binding or dissociation. Such a mechanical-relay picture thus provides a mechanistic underpinning for conformational changes, long-range communication, and inter-domain allostery in both proteins, where the responsive mechanical hotspots are mostly residues having important biological functions or significant mutation sensitivity.

Protein residues exhibit specific routes of mechanical relay as the adaptive responses to substrate binding or dissociation. On such physically contiguous connections, residues experience prominent changes in their coupling strengths.     

Generating 3D molecules conditional on receptor binding sites with deep generative models

The goal of structure-based drug discovery is to find small molecules that bind to a given target protein. Deep learning has been used to generate drug-like molecules with certain cheminformatic properties, but has not yet been applied to generating 3D molecules predicted to bind to proteins by sampling the conditional distribution of protein–ligand binding interactions. In this work, we describe for the first time a deep learning system for generating 3D molecular structures conditioned on a receptor binding site. We approach the problem using a conditional variational autoencoder trained on an atomic density grid representation of cross-docked protein–ligand structures. We apply atom fitting and bond inference procedures to construct valid molecular conformations from generated atomic densities. We evaluate the properties of the generated molecules and demonstrate that they change significantly when conditioned on mutated receptors. We also explore the latent space learned by our generative model using sampling and interpolation techniques. This work opens the door for end-to-end prediction of stable bioactive molecules from protein structures with deep learning.

We generate 3D molecules conditioned on receptor binding sites by training a deep generative model on protein–ligand complexes. Our model uses the conditional receptor information to make chemically relevant changes to the generated molecules.     

Visible light activated BINOL-derived chiroptical switches based on boron integrated hydrazone complexes

Chiral optical switches, which use light to control chirality in a reversible manner, offer unique properties and fascinating prospects in the areas of molecular switching and responsive systems, new photochromic materials and molecular data processing and storage. Herein, we report visible light responsive chiroptical switches based on tetrahedral boron coordination towards an easily accessible hydrazone ligand and optically pure BINOL. Upon instalment of a non-planar dibenzo[a,d]-cycloheptene moiety in the hydrazone ligand''s lower half, the enantiopure boron complex shows major chiroptical changes in the CD read-out after visible light irradiation. The thermal isomerization barrier in these chiroptical switching systems showed to be easily adjustable by the introduction of substituents onto the olefinic bond of the cycloheptene ring, giving profound control over their thermal stability. The control over their thermal stability in combination with excellent reversibility, photochemical properties and overall robustness of the complexes makes these BINOL-derived chiroptical switches attractive candidates for usage in advanced applications, e.g. photonic materials and nanotechnology.

Chiroptical switches, which use light to control chirality in a reversible manner, offer unique properties and fascinating prospects in the areas of molecular responsive systems, new photochromic materials and molecular data processing and storage.     

Designing light-driven rotary molecular motors

The ability to induce and amplify motion at the molecular scale has seen tremendous progress ranging from simple molecular rotors to responsive materials. In the two decades since the discovery of light-driven rotary molecular motors, the development of these molecules has been extensive; moving from the realm of molecular chemistry to integration into dynamic molecular systems. They have been identified as actuators holding great potential to precisely control the dynamics of nanoscale devices, but integrating molecular motors effectively into evermore complex artificial molecular machinery is not trivial. Maximising efficiency without compromising function requires conscious and judicious selection of the structures used. In this perspective, we focus on the key aspects of motor design and discuss how to manipulate these properties without impeding motor integrity. Herein, we describe these principles in the context of molecular rotary motors featuring a central double bond axle and emphasise the strengths and weaknesses of each design, providing a comprehensive evaluation of all artificial light-driven rotary motor scaffolds currently present in the literature. Based on this discussion, we will explore the trajectory of research into the field of molecular motors in the coming years, including challenges to be addressed, potential applications, and future prospects.

Various families of light-driven rotary molecular motors and the key aspects of motor design are discussed. Comparisons are made between the strengths and weaknesses of each motor. Challenges, applications, and future prospects are explored.     

A visible-light mediated ring opening reaction of alkylidenecyclopropanes for the generation of homopropargyl radicals

Classical cyclopropylcarbinyl radical clock reactions have been widely applied to conduct mechanistic studies for probing radical processes for a long time; however, alkylidenecyclopropanes, which have a similar molecular structure to methylcyclopropanes, surprisingly have not yet attracted researcher''s attention for similar ring opening radical clock processes. In recent years, photocatalytic NHPI ester activation chemistry has witnessed significant blooming developments and provided new synthetic routes for cross-coupling reactions. Herein, we wish to report a non-classical ring opening radical clock reaction using innovative NHPI esters bearing alkylidenecyclopropanes upon photoredox catalysis, providing a brand-new synthetic approach for the direct preparation of a variety of alkynyl derivatives. The potential synthetic utility of this protocol is demonstrated in the diverse transformations and facile synthesis of bioactive molecules or their derivatives and medicinal substances.

A non-classical ring opening radical clock reaction using the innovative NHPI esters bearing alkylidenecyclopropanes upon photoredox catalysis has been demonstrated, providing a brand-new synthetic approach to access a variety of alkynyl derivatives.     

Efficient construction of the hexacyclic ring core of palau'amine: the pKa concept for proceeding with unfavorable equilibrium reactions

Palau''amine has received a great deal of attention as an attractive synthetic target due to its intriguing molecular architecture and significant immunosuppressive activity, and we achieved its total synthesis in 2015. However, the synthesized palau''amine has not been readily applicable to the mechanistic study of immunosuppressive activity, because it requires 45 longest linear steps from a commercially available compound. Here, we report the short-step construction of the ABCDEF hexacyclic ring core of palau''amine. The construction of the CDE tricyclic ring core in a single step is achieved by our pK_a concept for proceeding with unfavorable equilibrium reactions, and a palau''amine analog without the aminomethyl and chloride groups is synthesized in 20 longest linear steps from the same starting material. The palau''amine analog is confirmed to retain the immunosuppressive activity. The present synthetic approach for a palau''amine analog has the potential for use in the development of palau''amine probes for mechanistic elucidation.

A palau''amine analog (2) was synthesized from 2-cyclopentenone in 20 steps. The construction of the CDE tricyclic ring core in a single step is achieved by our pK_a concept for proceeding with the unfavorable equilibrium reactions.