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Synthetic organic chemists are beginning to exploit electrochemical methods in increasingly creative ways. This is leading to a surge in productivity that is only now starting to take advantage of the full-potential of electrochemistry for accessing new structures in novel, more efficient ways. In this perspective, we provide insight into the potential of electrochemistry as a synthetic tool gained through studies of both direct anodic oxidation reactions and more recent indirect methods, and highlight how the development of new electrochemical methods can expand the nature of synthetic problems our community can tackle.

Proteins are the basic building blocks necessary for the operation and regulation of virtually all functions in living organisms. Over millions of years, evolution has created a vast repertoire of proteins finely tuned to execute their biological functions. However, biomedical and biotechnological applications often require protein properties and functions beyond the natural scope. To overcome this limitation, protein engineering methods have emerged which has enabled the targeted alteration and optimization of proteins. Driven by advances in structural biology and growing understanding of the structure-function relationship, the development of computational design methods has opened new possibilities for the design of functional proteins. Since many proteins carry out their functions through physical interactions with other proteins, the alteration or creation of protein-protein interactions (PPIs) represents a crucial aspect of functional protein design. The design of PPIs from scratch remains a substantial challenge, particularly when no structural data is available. To tackle this challenge, we showcase a novel strategy for the design of de novo PPIs by identifying complementary buried surfaces to a target interface using geometric deep learning, leveraging our knowledge from known protein complexes. Using this approach, we were able to show the design of de novo protein binders to two highly relevant targets. Computation-based functional protein design also holds great potential for the development of novel and more efficient vaccines to combat pathogens, like the influenza virus, that have yet been resisting traditional vaccine development efforts. The isolation of broadly neutralizing antibodies targeting the influenza hemagglutinin (HA) have guided vaccine development towards a conserved epitope on the stem domain. However, the low immunogenicity and complexity of this epitope hinders the robust and focused induction of these antibodies. Computational design of immunogens allows us to spotlight this epitope to elicit a targeted antibody response. By using a design approach that focuses on the mimicry of the molecular surface of the epitope, we were able to design an immunogen that elicits focused immune response cross-reactive to HA and able to activate cellular cytotoxicity in vitro. While this immunogen design focused on the induction of antibodies against the conserved stem domain of influenza HA, we also explored design routes to engineer antigens based on the variable head domain, known to induce very potent neutralizing antibodies. By exploiting the high structural similarity between head domains variable in sequence, we aim to construct novel chimeric head domains combining semi-conserved sites from two or more relevant HA subtypes. These immunogens bear great potential to induce heterosubtypic antibody responses by a single molecule, but also to further elucidate the immunodominance hierarchies on the HA head domain. Altogether, this work demonstrates the utilization of different computation-guided design strategies in combination with experimental fine-tuning and validation to develop new or re-engineered protein binders. The implemented strategies represent general frameworks that can be applied to the development of immunogens and other protein-based therapeutics.

Two isomorphous series including the adducts trans-[PdI2(CNC6H4-4-X)2]•2I2 [(1–3)•2I2; X = Cl 1, Br 2, I 3] and the complexes cis-[PdCl2(CNC6H4-4-X)(PPh3)] (4–6; X = Cl 4, Br 5, I 6) were characterized by X-ray crystallography. Inspection of the XRD data allowed the identification of halogen bonding C–X•••I–I in (1–3)•2I2 and C–X•••Cl–[Pd] in 4–6 thus providing a rare example of the triple Cl/Br/I exchange of -hole donating halogens. In accord with the conducted theoretical considerations, the strength of these XBs are in the range of 0.9–2.8 kcal/mol and these contacts are of noncovalent nature. The calculated maximum electrostatic potentials on the -hole donating X centers of CNC6H4-4-X on the 0.001 a.u. molecular surfaces for both (1–3)•2I2 and 4–6 series are increased along with the decrease of relative XB lengths. These data are consistent with Politzer and coworkers conclusions that are based exclusively on theoretical ground.

Phosphangulene (“Phang”) is an analogue of triphenylphosphine with a conical shape and electron-rich aromatic surface that complements the electron-poor surface of fullerenes, both geometrically and electronically. Large molecular surfaces with multiple areas of concavity can be made by grafting units of Phang onto selected cores, using the ability of phosphorus to form covalent bonds with many other elements. Incorporating multiple conical subunits of Phang creates molecules that are awkwardly shaped, unable to pack efficiently, and predisposed to form cocrystals. To demonstrate the potential of this approach, we made salts of the bis(phosphangulene)iminium cation ([(Phang)2N]+), in which the phosphorus atoms of two Phang groups are bonded to a single atom of nitrogen. Analysis of the structures of various salts shows that [(Phang)2N]+ has a unique ability to stabilize unusual anions, including those incorporating fullerenes.

The interactions between a wide variety of molecules having σ-holes or π-holes and several nitrogen bases have been analyzed computationally. The σ- and π-hole atoms span groups III–VII of the periodic table. The interaction energies range from quite weak, typical of non-covalent bonding, to unusually strong: from −4.6 to −22.0 kcal/mol for σ-hole bonding and from −4.0 to −42.4 kcal/mol for π-hole bonding. The markedly greater strengths of some bonds does not imply that any new factors or types of bonding are involved; they simply reflect higher degrees of the polarization that is part of any Coulombic interaction. To explain the stronger bonding, this polarization must be explicitly taken into account. We show that the interaction energies can be related quite well to (a) the maximum positive electrostatic potentials associated with the σ- or π-holes on their molecular surfaces, (b) the polarizabilities of the nitrogen bases, and especially (c) the polarizing electric fields of the σ- or π-hole molecules...

Molecular surfaces have comprehensive utility in the field of drug discovery. A deeper insight into different aspects of molecular surfaces is essential for the researchers to successfully identify a lead molecule with excellent pharmacokinetic profile. Therefore, the concept of molecular surfaces cannot be overlooked when designing a novel molecule. This is a better approach to correlate molecular surfaces with binding interaction, binding affinity, and their orientation, which in turn might produce information about the probable pharmacological potential. A profound knowledge of surface properties may provide more selective drugs in return, especially for the treatment of diseases where selectivity is the major issue associated with pathological conditions. This review sheds light on the various types of molecular surfaces, different visualization tools and their application in rationale drug designing. Moreover, this report also discloses the forthcoming perspectives of molecular surfaces that may create new ideas to deal with drug selectivity issues.

Evaluation of molecular surfaces plays the key role in a wide range of cutting-edge scientific fields and technologies, due to the well-characterized dependency between molecular surfaces and condensed phase thermodynamics. Numerous methods to evaluate molecular surfaces such as van-der-Waals and solvent accessible surface areas and various parameterizations for each one, have been proposed in the literature and typically yield quite diverse estimations of molecular surfaces. Despite this diversity, numerous successful applications have been reported for each one, which has become possible via ad-hoc modifications and parametrizations employed to accommodate inappropriately defined molecular surfaces. The main aim of the present study is to propose “thermodynamically effective” molecular surface which unlike the conventionally accepted molecular surfaces, can be defined only uniquely, can be measured experimentally for each molecule directly and straightforwardly, is defined based on a well-characterized theoretically described dependency between molecular surfaces and solution thermodynamics, and is highly accurate in evaluating various thermodynamics quantities in solution for a wide temperature range and different types of molecules, without requiring any ad-hoc modification.

COordinated Responsive Arrays of Surface-Linked polymer islands (CORALS) allow for the creation of molecular surfaces with novel and switchable properties. Critical components of CORALs are the uniformly distributed islands of densely grafted polymer chains (nanoislands) separated by regions of bare surface. The grafting footprint and separation distances of nanoislands are comparable to that of the constituent polymer chains themselves. Herein, we characterize the structural features of the nanoislands and semiflexible polymers within to better understand this critical constituent of CORALs. We observe different characteristics of grafted semiflexible polymers depending on the polymer island’s size and distance from the center of the island. Specifically, the characteristics of the chains at the island periphery are similar to isolated tethered polymer chains (full flexible chains), while chains in the center of the island experience the neighbor effect such as chains in the classic polymer brush. Chains close to the edge of the islands exhibit unique structural features between these two regimes. These results can be used in the rational design of CORALs with specific interfacial characteristics and predictable responses to external stimuli. It is hoped that this the discussion of the different morphologies of the polymers as a function of distance from the edge of the polymer will find applications in a wide variety of systems.

This paper presents the methods that have participated in the SHREC 2021 contest on retrieval and classification of protein surfaces on the basis of their geometry and physicochemical properties. The goal of the contest is to assess the capability of different computational approaches to identify different conformations of the same protein, or the presence of common sub-parts, starting from a set of molecular surfaces. We addressed two problems: defining the similarity solely based on the surface geometry or with the inclusion of physicochemical information, such as electrostatic potential, amino acid hydrophobicity, and the presence of hydrogen bond donors and acceptors. Retrieval and classification performances, with respect to the single protein or the existence of common sub-sequences, are analysed according to a number of information retrieval indicators.

Antibodies are proteins that recognize the molecular surfaces of potentially noxious molecules to mount an adaptive immune response or, in the case of autoimmune diseases, molecules that are part of healthy cells and tissues. Due to their binding versatility, antibodies are currently the largest class of biotherapeutics, with five monoclonal antibodies ranked in the top 10 blockbuster drugs. Computational advances in protein modelling and design can have a tangible impact on antibody-based therapeutic development. Antibody-specific computational protocols currently benefit from an increasing volume of data provided by next generation sequencing and application to related drug modalities based on traditional antibodies, such as nanobodies. Here we present a structured overview of available databases, methods and emerging trends in computational antibody analysis and contextualize them towards the engineering of candidate antibody therapeutics.

The Solvent Similarity Index (SSI) is a quantitative parameter we introduce for the comparison of the solvation properties of any solvent or solvent mixture. The Surface Site Interaction Model for Liquids at Equilibrium (SSIMPLE) was used to calculate the free energy of solvation of a single Surface Site Interaction Point (SSIP) on a solute. The SSIP representation of molecular surfaces was used to calculate the free energy of solvation for all possible solute polarities, generating a unique solvation profile for any solvent or solvent mixture. Quantitative comparison of the solvation profiles of two solvents was used as the basis for calculating the solvation similarity index. Values of SSI were calculated for all pairwise comparisons of 261 pure solvents at 298 K, and the results were used to classify solvents into groups according to their solvation properties. Applications to understanding the solvation properties of binary solvent mixtures and for identification of alternative solvents are illustrated.

sensaas is a tool developed for aligning and comparing molecular shapes and sub‐shapes. Alignment is obtained by registration of 3D point‐based representations of the van der Waals surface. The method uses local properties of the shape to identify the correspondence relationships between two point clouds containing up to several thousand colored (labeled) points. Our rigid‐body superimposition method follows a two‐stage approach. An initial alignment is obtained by matching pose‐invariant local 3D descriptors, called FPFH, of the input point clouds. This stage provides a global superimposition of the molecular surfaces, without any knowledge of their initial pose in 3D space. This alignment is then refined by optimizing the matching of colored points. In our study, each point is colored according to its closest atom, which itself belongs to a user defined physico‐chemical class. Finally, sensaas provides an alignment and evaluates the molecular similarity by using Tversky coefficients. To assess the efficiency of this approach, we tested its ability to reproduce the superimposition of X‐ray structures of the benchmarking AstraZeneca (AZ) data set and, compared its results with those generated by the two shape‐alignment approaches shaep and shafts. We also illustrated submatching properties of our method with respect to few substructures and bioisosteric fragments. The code is available upon request from the authors (demo version at https://chemoinfo.ipmc.cnrs.fr/SENSAAS).

Many fullerenes and carbon nanotubes have the very large electrophilic regions on their molecular surfaces. The existence of these large electrophilic regions is beyond the scope of the concept of the σ-hole and π-hole which were introduced to describe the formation of the noncovalent bonds. The inner cavities of many fullerenes and carbon nanotubes are the regions of positive electrostatic potential, and are electron-withdrawing in character. Our results clearly show that it is the electron-withdrawing cavity not the curvature of the fullerene or carbon nanotube that plays a dominant role for the formation of the large electrophilic regions on the molecular surface. The important role of the large electrophilic regions of fullerenes has been illustrated by using them to successfully explain some experimental observations in crystal engineering.

A protein and a ligand have a process of recognizing each other when they are remote before approaching for binding. In this process, there should be a local portion corresponding to a target of the recognition (a recognition spot) on the protein molecular surface. In this paper, we proposed a new biclustering algorithm BISERS for predicting recognition spots on protein molecular surfaces, in which a portion of the molecular surface of a query protein that frequently shows the similarity to other specific proteins binding to the similar ligand is extracted by biclustering. In BISERS, the similarity between rows as well as the similarity between columns is introduced into the evaluation function for updating the biclusters. In addition, the random sampling is applied to the process of exclusive selection of the column for reducing the computational cost effectively. Experimental results for 60 proteins show the effectiveness of our BISERS algorithm.

The Protein Data Bank Japan (PDBj), a member of the worldwide Protein Data Bank (wwPDB), accepts and processes the deposited data of experimentally determined biological macromolecular structures. In addition to archiving the PDB data in collaboration with the other wwPDB partners, PDBj also provides a wide range of original and unique services and tools, which are continuously improved and updated. Here, we report the new RDB PDBj Mine 2, the WebGL molecular viewer Molmil, the ProMode-Elastic server for normal mode analysis, a virtual reality system for the eF-site protein electrostatic molecular surfaces, the extensions of the Omokage search for molecular shape similarity, and the integration of PDBj and BMRB searches.

We propose to characterise the “impenetrable” volumes of molecules A and B in a complex A---B by finding that contour of its electronic density that separates the molecular surfaces of A and B but leaves them almost touching. The volume of the complex within that contour is always less than within the 0.001 au contour. The percent difference measures the interpenetration of the two molecules at equilibrium, and is found to directly correlate with the binding energy of the complex. We interpret the volume of each molecule that is enclosed by the almost-touching contour as that molecule's impenetrable volume relative to its particular partner. The percents by which the molecules' relative impenetrable volumes differ from their 0.001 au volumes in the free states also correlate with the strengths of the interactions. This allows the “absolute” impenetrable volume of any molecule to be estimated as ∼25% of its 0.001 au volume in the free state. However this absolute impenetrable volume is only approac...

Predicting interactions between proteins and other biomolecules solely based on structure remains a challenge in biology. A high-level representation of protein structure, the molecular surface, displays patterns of chemical and geometric features that fingerprint a protein's modes of interactions with other biomolecules. We hypothesize that proteins participating in similar interactions may share common fingerprints, independent of their evolutionary history. Fingerprints may be difficult to grasp by visual analysis but could be learned from large-scale datasets. We present MaSIF (molecular surface interaction fingerprinting), a conceptual framework based on a geometric deep learning method to capture fingerprints that are important for specific biomolecular interactions. We showcase MaSIF with three prediction challenges: protein pocket-ligand prediction, protein-protein interaction site prediction and ultrafast scanning of protein surfaces for prediction of protein-protein complexes. We anticipate that our conceptual framework will lead to improvements in our understanding of protein function and design.

Molecular visualization is often challenged with rendering of large molecular structures in real time. The key to LOD (level-of-detail), a classical technology, lies in designing a series of hierarchical abstractions of protein. In the paper, we improved the smoothness of transition for these abstractions by constructing a complete binary tree of a protein. In order to reduce the degree of expansion of the geometric model corresponding to the high level of abstraction, we introduced minimum ellipsoidal enveloping and some post-processing techniques. At the same time, a simple, ellipsoid drawing method based on graphics processing unit (GPU) is used that can guarantee that the drawing speed is not lower than the existing sphere-drawing method. Finally, we evaluated the rendering performance and effect on series of molecules with different scales. The post-processing techniques applied, diffuse shading and contours, further conceal the expansion problem and highlight the surface details.

In this short review, an electroorganic synthesis approach to the construction of addressable, complex molecular surfaces is described along with the parameters that guided the development of that synthetic approach. The result of the work is a synthetic toolbox that will allow microelectrode arrays to be used for the "real-time" monitoring of small molecule interactions with biological targets.

Sum-frequency generation vibrational spectroscopy (SFG-VS) was first developed in the 1980s and it has been proven a uniquely sensitive and surface/interface selective spectroscopic probe for characterization of the structure, conformation and dynamics of molecular surfaces and interfaces. In recent years, there have been many progresses in the development of methodology and instrumentation in the SFG-VS toolbox that have significantly broadened the application to complex molecular surfaces and interfaces. In this review, after presenting a unified view on the theory and methodology focusing on the SFG-VS spectral lineshape, as well as the new opportunities in SFG-VS applications with such developments, some of the controversial issues that have been puzzling the community are discussed. The aim of this review is to present to the researchers and students interested in molecular surfaces and interfacial sciences up-to-date perspectives complementary to the existing textbooks and reviews on SFG-VS.

We have computed the most positive and most negative values of the electrostatic potentials on the surfaces of a series of molecules, some of which contain atoms from the second and third rows of Groups IV, VI and VII. Three different methods were used – Hartree-Fock and the density functional B3LYP and M06-2X – in conjunction with numerous basis sets of various sizes. Our objectives were (a) to assess the degrees to which the different procedures gave comparable results, and (b) to ascertain which procedures best combine reliability with computational efficiency. Our primary conclusions were: (a) For a given basis set, the three methods give essentially comparable results. (b) Hydrogens do not require either polarization or diffuse functions, not even when the potential of interest is on the hydrogen. (c) Polarization functions are essential, for first-row as well as higher-row atoms; diffuse functions are less important. (d) The recommended basis set for electrostatic potential calculations, of those investigated, is the 6-31G*. Larger basis sets are not needed for this purpose. (e) If the 6-31G* is precluded (e.g. by the size of the system or by the presence of fourth-row atoms), then the 3-21G* is likely to be an acceptable alternative.

Here we present a guide to ion mobility mass spectrometry experiments, which covers both linear and nonlinear methods: what is measured, how the measurements are done, and how to report the results, including the uncertainties of mobility and collision cross section values. The guide aims to clarify some possibly confusing concepts, and the reporting recommendations should help researchers, authors and reviewers to contribute comprehensive reports, so that the ion mobility data can be reused more confidently. Starting from the concept of the definition of the measurand, we emphasize that (i) mobility values (K-0) depend intrinsically on ion structure, the nature of the bath gas, temperature, and E/N; (ii) ion mobility does not measure molecular surfaces directly, but collision cross section (CCS) values are derived from mobility values using a physical model; (iii) methods relying on calibration are empirical (and thus may provide method-dependent results) only if the gas nature, temperature or E/N cannot match those of the primary method. Our analysis highlights the urgency of a community effort toward establishing primary standards and reference materials for ion mobility, and provides recommendations to do so. (c) 2019 The Authors. Mass Spectrometry Reviews Published by Wiley Periodicals, Inc.

The molecular surface has been suggested to be a region of the molecule, where information of non-covalent intermolecular interactions is present. Many workers have pursued this idea by constructing models based on statistical parameters Φ extracted from the electrostatic potential on a particular molecular surface. We claim that a better approach is to define a family of equivalent molecular surfaces, each associated with a particular electron density e. The demand that any model must give the same predictions on all such molecular surfaces yields a mathematical requirement restricting the space of permissible parameters. We prove that linear single-variable models of the form property = α Φ + β will only yield invariant predictions if the parameter values of Φ computed on equivalent surfaces are linearly related. This claim is not restricted to the use of the electrostatic potential, but holds for any parameter extracted from the surface of molecules. By using a set of 44 molecules, we also demo...

The important role that electrostatic potentials computed on molecular surfaces can have in designing new materials via co-crystallization is discussed and illustrated. The locally most positive and most negative values of the surface electrostatic potential identify and rank sites for hydrogen bonding (complementing Etter’s rules), halogen bonding, and other types of noncovalent interactions. It is shown that the primary interactions are often better viewed as involving small regions rather than specific atoms. Recent applications of cocrystallization as a means of reducing the hazard associated with energetic materials are briefly examined.