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SARS-CoV-2 remains a health threat with the continuous emergence of new variants. This work aims to expand the knowledge about the SARS-CoV-2 receptor-binding domain (RBD) interactions with cell receptors and monoclonal antibodies (mAbs). By using constant-pH Monte Carlo simulations, the free energy of interactions between the RBD from different variants and several partners (Angiotensin-Converting Enzyme-2 (ACE2) polymorphisms and various mAbs) were predicted. Computed RBD-ACE2-binding affinities were higher for two ACE2 polymorphisms (rs142984500 and rs4646116) typically found in Europeans which indicates a genetic susceptibility. This is amplified for Omicron (BA.1) and its sublineages BA.2 and BA.3. The antibody landscape was computationally investigated with the largest set of mAbs so far in the literature. From the 32 studied binders, groups of mAbs were identified from weak to strong binding affinities (e.g. S2K146). These mAbs with strong binding capacity and especially their combination are amenable to experimentation and clinical trials because of their high predicted binding affinities and possible neutralization potential for current known virus mutations and a universal coronavirus.Communicated by Ramaswamy H. Sarma.

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Gold nanoparticles (AuNPs) are attractive structures for biosensing, most due to different properties at nanoscale and biocompatibility. Localized surface plasmon resonance (LSPR) is one of these properties; LSPR enable the electromagnetic field enhancement closer to metallic surface, which allows surface-enhanced spectroscopies, like surface enhanced fluorescence (SEF). In this study, an immuno-biosensor based on gold nanorods (AuNRs) and SEF was constructed for simple and fast analysis to detect albumin antibody (anti-BSA) using antigen-antibody (anti-BSA/BSA) interaction as the biorecognition model. AuNRs were presented in two distinct configurations, in suspension (S-AuNRs) and adsorbed on glass slides (AuNRs-chip), and the detection was performed through an extrinsic method, wherein the SEF signal of a reporter molecule (IR-820 cyanine-type dye) was monitored. The analyte detection was evidenced by SEF mapping, where the average signal in the presence of anti-BSA was three times more intense than for the assay in the absence of analyte. A digital protocol was proposed to simplify the spectroscopic data analysis and reduce the intensity variability; in this protocol the number of positive events in the presence of anti-BSA is much larger (around two times) compared to the absence of analyte. The AuNRs based SEF immuno-biosensor allowed an efficient and simple analysis with specific biorecognition and may contribute as an efficient spectroscopy platform for immuno-biosensing.

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Sucrose is a primary metabolite in plants, a source of energy, a source of carbon atoms for growth and development, and a regulator of biochemical processes. Most of the traditional analytical chemistry methods for sucrose quantification in plants require sample treatment (with consequent tissue destruction) and complex facilities, that do not allow real-time sucrose quantification at ultra-low concentrations (nM to pM range) under in vivo conditions, limiting our understanding of sucrose roles in plant physiology across different plant tissues and cellular compartments. Some of the above-mentioned problems may be circumvented with the use of bio-compatible ligands for molecular recognition of sucrose. Nevertheless, problems such as the signal-noise ratio, stability, and selectivity are some of the main challenges limiting the use of molecular recognition methods for the in vivo quantification of sucrose. In this review, we provide a critical analysis of the existing analytical chemistry tools, biosensors, and synthetic ligands, for sucrose quantification and discuss the most promising paths to improve upon its limits of detection. Our goal is to highlight the criteria design need for real-time, in vivo, highly sensitive and selective sucrose sensing capabilities to enable further our understanding of living organisms, the development of new plant breeding strategies for increased crop productivity and sustainability, and ultimately to contribute to the overarching need for food security.

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Coffee, a beverage with a complex chemical composition, is appreciated for the sensory experience of its taste and aroma. The compound 5-(hydroxymethyl)-2-furfural (HMF) is essential for sensory characterization of the beverage, and is also used in the traceability of its production. In this work, a procedure combining salting-out assisted liquid-liquid extraction (SALLE) and an electropolymerized molecularly imprinted polymer (e-MIP) was developed for the detection and quantification of HMF in coffee samples. The sample preparation step using SALLE employed a combination of acetonitrile and phosphate-buffered saline, in a proportion of 70:30 (ACN:PBS), with addition of 0.02 g of NaCl. The new sensor (e-MIP) was prepared by electropolymerization of p-aminobenzoic acid onto a glassy carbon electrode (GCE) using cyclic voltammetry (CV). Analytical determinations were performed by differential pulse voltammetry (DPV). The linear regression correlation coefficient (r2) for the response was 0.9986. The limits of detection and quantification were 0.372 mg L-1 and 1.240 mg L-1, respectively. The repeatability and reproducibility values obtained were 6 and 10%, respectively. The recoveries for three concentration levels were between 97 and 101%. Analyses of different coffee samples showed that the HMF concentrations varied from 261.0 ± 41.0 to 770.2 ± 55.9 mg kg-1 in powdered coffee samples, and from 1510 ± 50 to 4445 ± 278 mg kg-1 in instant coffee samples. The advantages of this procedure, compared to other methods described in the literature, are its simplicity, easy operation, good selectivity and sensitivity, low cost, and minimal use of organic solvents.

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A pseudo-rotaxane is a host-guest complex composed of a linear molecule encircled by a macrocyclic ring. These complexes can be assembled by sliding the host over the guest terminal groups. If there is a close match between the molecular volume of the flanking groups on the guest and the cavity size of the macrocycle, the slipping might occur slowly or even become completely hindered. We have previously shown that it is possible to overcome the restraints imposed by steric effects on the sliding process by integrating electrostatic attractive interactions during the slipping step. In this work, we extend our electrostatically assisted slipping approach (EASA) to a new host-guest system featuring a flexible macrocyclic ring and a series of asymmetric guests containing a cyclic tertiary ammonium group. Compelling evidence for pseudo-rotaxane formation is presented, along with thermodynamic and kinetic data. Experimental results suggests that the higher conformational flexibility of 24-crown-8 significantly increases the sliding rate, compared with the more rigid dibenzo-24-crown-8, without affecting complex stability. Furthermore, by combining the EASA and macrocycle flexibility, we were capable to slip a large eight-membered cyclic group across the 24-crown-8 annulus, setting a new limit on the ring molecular size that can pass through a 24-membered crown ether.

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The incorporation of a guest, with different basic sites, into an organized system (host), such as macrocycles, could stabilize, detect, or promote the formation of a certain protomer. In this context, this work aimed to study the influence of cucurbit[7]uril (CB7) on dyes such as 7-(dimethylamino)-aza-coumarins, which have more than one basic site along their molecular structure. For this, three 3-styryl derivatives of 7-(dialkylamino)-aza-coumarin dyes (SAC1-3) were synthesized and characterized by NMR, ESI-HRMS and IR. The spectral behaviour of the SACs in the absence and presence of CB7 was studied. The results showed large shifts in the UV-vis spectrum in acid medium: a hypsochromic shift of ≈5400 cm-1 (SAC1-2) and ≈3500 cm-1 (SAC3) in the absence of CB7 and a bathochromic shift of ≈4500 cm-1 (SAC1-3) in the presence of CB7. The new absorptions at long and short wavelengths were assigned to the corresponding protomers by computational calculations at the density functional theory (DFT) level. Additionally, the binding mode was corroborated by molecular dynamics simulations. Findings revealed that in the presence of CB7 the heterocyclic nitrogen was preferably protonated instead of the dialkylamino group. Namely, CB7 induces a change in the protonation preference at the basic sites of the SACs, as consequence of the molecular recognition by the macrocycle.

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Capillary electromigration is a well-established commercial group of analytical techniques, and, alike other column separation systems, it often benefits from a preceding sample preparation step. This step not only improves the analytical performance of many methods and prolongs the equipment's life span, but it also makes some determinations possible. A remarkable sample preparation technique is molecular imprinting technology: by creating tailored polymers able to 'select' the targeted analytes, matrix effects are severely diminished. This review aims to provide an overview of all the published works that combine capillary electrophoresis and molecularly imprinted polymers (MIP). Although a literature search produced around 130 published analytical methodologies and 5 patents, authors believe that there is still plenty of room for interesting developments. Works ranged from the analysis of pesticides to pharmaceuticals or hormones, being the most common instrumental detection spectrophotometric. The combination between MIP and electrophoresis can be divided into two main categories depending on where the MIPs are placed within the analytical 'pipeline': off-column and in-column. Off-column consisted of MIP batch application previous to capillary injection. In-column approaches are more complex, and can be divided into coating, monolith, packed (these three being considered capillary electrochromatography), and dispersed particles (affinity capillary electrophoresis).

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Antibiotics, although being amazing compounds, need to be monitored in the environment and foodstuff. This is primarily to prevent the development of antibiotic resistance that may make them ineffective. Unsurprisingly, advances in analyticalsciences that can improve their determination are appreciated. Electrochemical techniques are known for their simplicity, sensitivity, portability and low-cost; however, they are often not selective enough without recurring to a discriminating element like an antibody. Molecular imprinting technology aims to create artificial tissues mimicking antibodies named molecularly imprinted polymers (MIPs), these retain the advantages of selectivity but without the typical disadvantages of biological material, like limited shelf-life and high cost. This manuscript aims to review all analytical methodologies for antibiotics, using MIPs, where the detection technique is electrochemical, like differential pulse voltammetry (DPV), square-wave voltammetry (SWV) or electrochemical impedance spectroscopy (EIS). MIPs developed by electropolymerization (e-MIPs) were applied in about 60 publications and patents found in the bibliographic search, while MIPs developed by other polymerization techniques, like temperature assisted ("bulk") or photopolymerization, were limited to around 40. Published works covered the electroanalysis of a wide range of different antibiotics (ß-lactams, tetracyclines, quinolones, macrolides, aminoglycosides, among other), in a wide range of matrices (food, environmental and biological).

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The assembly of a septin filament requires that homologous monomers must distinguish between one another in establishing appropriate interfaces with their neighbors. To understand this phenomenon at the molecular level, we present the first four crystal structures of heterodimeric septin complexes. We describe in detail the two distinct types of G-interface present within the octameric particles, which must polymerize to form filaments. These are formed between SEPT2 and SEPT6 and between SEPT7 and SEPT3, and their description permits an understanding of the structural basis for the selectivity necessary for correct filament assembly. By replacing SEPT6 by SEPT8 or SEPT11, it is possible to rationalize Kinoshita's postulate, which predicts the exchangeability of septins from within a subgroup. Switches I and II, which in classical small GTPases provide a mechanism for nucleotide-dependent conformational change, have been repurposed in septins to play a fundamental role in molecular recognition. Specifically, it is switch I which holds the key to discriminating between the two different G-interfaces. Moreover, residues which are characteristic for a given subgroup play subtle, but pivotal, roles in guaranteeing that the correct interfaces are formed.

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Polyamine-salt aggregates (PSA) are biomimetic soft materials that have attracted great attention due to their straightforward fabrication methods, high drug-loading efficiencies, and attractive properties for pH-triggered release. Herein, a simple and fast multicomponent self-assembly process was used to construct cross-linked poly(allylamine hydrochloride)/phosphate PSAs (hydrodynamic diameter of 360 nm) containing glucose oxidase enzyme, as a glucose-responsive element, and human recombinant insulin, as a therapeutic agent for the treatment of diabetes mellitus (GI-PSA). The addition of increasing glucose concentrations promotes the release of insulin due to the disassembly of the GI-PSAs triggered by the catalytic in situ formation of gluconic acid. Under normoglycemia, the GI-PSA integrity remained intact for at least 24 h, whereas hyperglycemic conditions resulted in 100 % cargo release after 4 h of glucose addition. This entirely supramolecular strategy presents great potential for the construction of smart glucose-responsive delivery nanocarriers.

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Molecular recognition of saccharides is a growing field, which has many implications in cancer therapy, drug discovery, and cellular communication among others. The participation of CH/π interactions in this event is well known. Nevertheless, the intrinsic role of CH/π for modulating chemical reactions is still far from being applicable. In this experimental and computational work we have evaluated the participation of CH/π interactions in the aminolysis reaction of acetyl galactoside promoted with different 6-substituted 2(1H)-pyridones. Two features have been incorporated to the promoter molecular structure, on one end the promoting pyridone group and on the other end the recognition moiety, joined together by an alkyne spacer. The small increment in the observed pseudo-first-order rate constant values (kobs) was related to the stability of the transition state provided by noncovalent interactions, including CH/π interactions. A longer alkyne spacer was necessary to improve the molecular recognition of the galactoside substrate. The trend of the calculated activation energy values (ΔERTS) was in good accordance with the experimental rate constant values.

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Protein-ligand docking simulations are of central interest for computer-aided drug design. Docking is also of pivotal importance to understand the structural basis for protein-ligand binding affinity. In the last decades, we have seen an explosion in the number of three-dimensional structures of protein-ligand complexes available at the Protein Data Bank. These structures gave further support for the development and validation of in silico approaches to address the binding of small molecules to proteins. As a result, we have now dozens of open source programs and web servers to carry out molecular docking simulations. The development of the docking programs and the success of such simulations called the attention of a broad spectrum of researchers not necessarily familiar with computer simulations. In this scenario, it is essential for those involved in experimental studies of protein-ligand interactions and biophysical techniques to have a glimpse of the basics of the protein-ligand docking simulations. Applications of protein-ligand docking simulations to drug development and discovery were able to identify hits, inhibitors, and even drugs. In the present chapter, we cover the fundamental ideas behind protein-ligand docking programs for non-specialists, which may benefit from such knowledge when studying molecular recognition mechanism.

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Since the early 1980s, we have witnessed considerable progress in the development and application of docking programs to assess protein-ligand interactions. Most of these applications had as a goal the identification of potential new binders to protein targets. Another remarkable progress is taking place in the determination of the structures of protein-ligand complexes, mostly using X-ray diffraction crystallography. Considering these developments, we have a favorable scenario for the creation of a computational tool that integrates into one workflow all steps involved in molecular docking simulations. We had these goals in mind when we developed the program SAnDReS. This program allows the integration of all computational features related to modern docking studies into one workflow. SAnDReS not only carries out docking simulations but also evaluates several docking protocols allowing the selection of the best approach for a given protein system. SAnDReS is a free and open-source (GNU General Public License) computational environment for running docking simulations. Here, we describe the combination of SAnDReS and AutoDock4 for protein-ligand docking simulations. AutoDock4 is a free program that has been applied to over a thousand receptor-ligand docking simulations. The dataset described in this chapter is available for downloading at https://github.com/azevedolab/sandres.

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Computational analysis of protein-ligand interactions is of pivotal importance for drug design. Assessment of ligand binding energy allows us to have a glimpse of the potential of a small organic molecule as a ligand to the binding site of a protein target. Considering scoring functions available in docking programs such as AutoDock4, AutoDock Vina, and Molegro Virtual Docker, we could say that they all rely on equations that sum each type of protein-ligand interactions to model the binding affinity. Most of the scoring functions consider electrostatic interactions involving the protein and the ligand. In this chapter, we present the main physics concepts necessary to understand electrostatics interactions relevant to molecular recognition of a ligand by the binding pocket of a protein target. Moreover, we analyze the electrostatic potential energy for an ensemble of structures to highlight the main features related to the importance of this interaction for binding affinity.

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Fast and reliable evaluation of the hydrogen bond potential energy has a significant impact in the drug design and development since it allows the assessment of large databases of organic molecules in virtual screening projects focused on a protein of interest. Semi-empirical force fields implemented in molecular docking programs make it possible the evaluation of protein-ligand binding affinity where the hydrogen bond potential is a common term used in the calculation. In this chapter, we describe the concepts behind the programs used to predict hydrogen bond potential energy employing semi-empirical force fields as the ones available in the programs AMBER, AutoDock4, TreeDock, and ReplicOpter. We described here the 12-10 potential and applied it to evaluate the binding affinity for an ensemble of crystallographic structures for which experimental data about binding affinity are available.

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X-ray diffraction crystallography is the primary technique to determine the three-dimensional structures of biomolecules. Although a robust method, X-ray crystallography is not able to access the dynamical behavior of macromolecules. To do so, we have to carry out molecular dynamics simulations taking as an initial system the three-dimensional structure obtained from experimental techniques or generated using homology modeling. In this chapter, we describe in detail a tutorial to carry out molecular dynamics simulations using the program NAMD2. We chose as a molecular system to simulate the structure of human cyclin-dependent kinase 2.

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Molecular docking is the major computational technique employed in the early stages of computer-aided drug discovery. The availability of free software to carry out docking simulations of protein-ligand systems has allowed for an increasing number of studies using this technique. Among the available free docking programs, we discuss the use of ArgusLab ( http://www.arguslab.com/arguslab.com/ArgusLab.html ) for protein-ligand docking simulation. This easy-to-use computational tool makes use of a genetic algorithm as a search algorithm and a fast scoring function that allows users with minimal experience in the simulations of protein-ligand simulations to carry out docking simulations. In this chapter, we present a detailed tutorial to perform docking simulations using ArgusLab.

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Homology modeling is a computational approach to generate three-dimensional structures of protein targets when experimental data about similar proteins are available. Although experimental methods such as X-ray crystallography and nuclear magnetic resonance spectroscopy successfully solved the structures of nearly 150,000 macromolecules, there is still a gap in our structural knowledge. We can fulfill this gap with computational methodologies. Our goal in this chapter is to explain how to perform homology modeling of protein targets for drug development. We choose as a homology modeling tool the program MODELLER. To illustrate its use, we describe how to model the structure of human cyclin-dependent kinase 3 using MODELLER. We explain the modeling procedure of CDK3 apoenzyme and the structure of this enzyme in complex with roscovitine.

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Molecular recognition of the amphiphilic electron carrier ubiquinone (Q) by respiratory complexes is a fundamental part of electron transfer chains in mitochondria and bacteria. The primary respiratory complex I binds Q in a long and narrow protein chamber to catalyse its reduction. But, the binding mechanism and the role of chamber hydration in substrate selectivity and stability are unclear. Here, large-scale atomistic molecular dynamics simulations and estimated free energy profiles are used to characterize in detail the binding mechanism to complex I of Q with short and with long isoprenoid tails. A highly stable binding site with two different poses near the chamber exit and a secondary reactive site near the N2 iron-sulfur cluster are found which may lead to an alternative Q redox chemistry and help to explain complex I reactivity. The binding energetics depends mainly on polar interactions of the Q-head and on the counterbalanced hydration of Q-tail isoprenoid units and hydrophobic residues inside the protein chamber. Selectivity upon variation of tail length arises by shifting the hydration balance. This internal hydration mechanism may have implications for binding of amphiphilic molecules to cavities in other membrane proteins.

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Ligand efficiency is a widely used design parameter in drug discovery. It is calculated by scaling affinity by molecular size and has a nontrivial dependency on the concentration unit used to express affinity that stems from the inability of the logarithm function to take dimensioned arguments. Consequently, perception of efficiency varies with the choice of concentration unit and it is argued that the ligand efficiency metric is not physically meaningful nor should it be considered to be a metric. The dependence of ligand efficiency on the concentration unit can be eliminated by defining efficiency in terms of sensitivity of affinity to molecular size and this is illustrated with reference to fragment-to-lead optimizations. Group efficiency and fit quality are also examined in detail from a physicochemical perspective. The importance of examining relationships between affinity and molecular size directly is stressed throughout this study and an alternative to ligand efficiency for normalization of affinity with respect to molecular size is presented.