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Odorous dioxanes and dioxolanes, a class of cyclic acetals often produced as byproducts in polyester resin manufacturing, are problematic in drinking water treatment due to their low odor thresholds and resistance to conventional treatment technology. Our research focuses on the removal of ten dioxane/dioxolane compounds through oxidation and adsorption processes, exploring the key molecular properties that govern the treatmentability. We discovered that both chlorination and permanganate oxidation were largely ineffective at degrading cyclic acetals, achieving less than 20% removal even at high applicable doses. Conversely, powdered activated carbon (PAC) adsorption proved to be a more effective method, with a removal of > 90% at a PAC dosage of 10 mg/L for seven out of ten compounds. The presence of natural organic matter (NOM) reduced PAC adsorbability for all odorants, but the deterioration level substantially varied and mostly affected by structural flexibility as indicated by the number of rotatable bonds. The results of both the experimental investigation and molecular simulation corroborated the hypothesis that more rotatable bonds (from one to three here) are indicative of greater structural flexibility, which in consequence determines the susceptibility of cyclic acetals to NOM competitive adsorption. Increased structural flexibility could facilitate greater entry into silt-like micropores or achieve preferential adsorption sites with more compatible morphology against NOM competition. When pre-oxidation (chlorination and permanganate oxidation) and adsorption were applied sequentially, additional low molecular weight NOM components produced by pre-oxidation resulted in intensified NOM competition and decreased odorant adsorbability. If this combination is inevitably required for algae and odorant control, it would be beneficial to utilize a wise screen for oxidants and a reduced oxidant dose (less than 2 mg/L) to mitigate the deterioration of odorant adsorption. This study elucidates the roles of structural flexibility in influencing the treatability of dioxanes and dioxolanes, extending beyond the solely well-established effects of hydrophobicity. It also presents rational practice guidelines for the combination of pre-oxidation and adsorption in addressing odor incidents associated with dioxane and dioxolane compounds.

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The preparation of capsid-like nanoshells and the elucidation of their formation pathways are crucial for the application potential of capsid-like nanomaterials. In this study, we have prepared biomimetic capsid-like nanoshells (CLNs) through the solution self-assembly of poly (ß-phenethyl-L-aspartate) homopolypeptide (PPLA). The formation of CLNs is governed by an aggregation-fusion mechanism. Initially, PPLA molecules self-assemble into small spherical assemblies as subunits and the initial nuclei are formed through fusing some subunits. Subsequently, additional subunits rapidly fuse onto these nuclei, leading to the growth of full or partial CLNs during the growth phase. Moreover, the suitable condition benefiting CLNs formation is clarified by a morphological phase diagram based on the initial PPLA concentration against water content. Molecular-level measurements suggest that the molecular flexibility of PPLA is a key factor in the arrangement and fusion of subunits for the formation of CLNs. These findings offer new perspectives for a deeper understanding of the formation pathways of capsid-like nanoshells derived from synthetic polymers.

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Yalkowsky's General Solubility Equation (GSE), with its three fixed constants, is popular and easy to apply, but is not very accurate for polar, zwitterionic, or flexible molecules. This review examines the findings of a series of studies, where we have sought to come up with a better prediction model, by comparing the performances of the GSE to Abraham's Solvation Equation (ABSOLV), and Random Forest regression (RFR) machine-learning (ML) method. Large, well-curated aqueous intrinsic solubility databases are available. However, drugs may be sparsely distributed in chemical space, concentrated in clusters. Even a large database might overlook some regions. Test compounds from under-represented portions of space may be poorly predicted, as might be the case with the 'loose' set of 32 drugs in the Second Solubility Challenge (2020). There appears to be still a need for better coverage of drug space. Increasingly, current trends in predictions of solubility use calculated input descriptors, which may be an advantage for exploring properties of molecules yet to be synthesized. The risk may be that overall prediction approaches might be based on accumulated uncertainty. The increasing use of ML/AI methods can lead to accurate predictions, but such predictions may not readily suggest the strategies to pursue in selecting yet-to-be-synthesized compounds. Based on our latest findings, we recommend predictions based on both 'grouped' ABSOLV(GRP) and 'Flexible Acceptor' GSE(Φ,B) models with the provided best-fit parameters, where Φ is the Kier molecular flexibility index and B is the Abraham H-bond acceptor strength. For molecules with Φ < 11, the prudent choice is to pick the Consensus Model, the average of ABSOLV(GRP) and GSE(Φ,B). For more flexible molecules, GSE(Φ,B) is recommended.

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CONTEXT: A large number of heterocyclic compounds are used as drugs, mainly due to the duality of lipophilicity playing in hydrophobic interactions and solubility with at least one hydrogen bond acceptor. The study of electronic properties is then important to better understand not only these charge distribution effects but also some other physicochemical properties involved in bioactivity to directly assess the bioavailability of these compounds and a possible classification in related applications. Phytomolecules such as chromenes are very accessible molecules exhibiting a bioactivity. Our study is focused on the impact of a number of functional groups acting on some 2,2-dimethylchromene derivatives, namely their global reactivity from the frontier molecular orbitals and local reactivity from the Fukui functions, where the carbonyl group acting as an electron withdrawal group has the most relevant effect, the solubility from the partition coefficient Log P strongly depending on the charge distribution and electronegative sites, the optical effects from the delocalization in the vinyl group, as well as the evaluation of the entropy associated with the molecular flexibility also acting on the bioactivity. Despite the effects of the wave function or density methods on the order of magnitude of these properties, these compounds are consistent with the rules for a potential oral drug candidate. METHODS: The calculations of the electronic properties were performed through two levels of theory: Hartree-Fock level as a wave function-based method as an ab initio reference including some physically consistent eigenvalues and density functional theory DFT as a correlation consistent method using different functionals: hybrid or with a long-range correction. The basis set used is a 6-311++G(d,p) Pople basis set including diffuse and polarization basis functions. The basis set is adapted to the size of the molecules and consequently to the degree of electronic localization. Gaussian 09 software was used for the computation.

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Crystal polymorphs of fluorinated ionic liquids (fILs) were examined at low-temperature (LT) by Raman spectroscopy. The fILs were 1-alkyl-3-methylimidazolium perfluorobutanesulfonate, [Cnmim][PFBS] (n = 4, 6, and 8). The cations and anion possess conformational degrees of freedom. Various LT phases were derived from the conformational polymorphs of the cations and the anion. Conformational flexibility depended on alkyl chain length. The crystal polymorphs in the fILs were sensitive to molecular conformations and flexibility.

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Detergents have been major contributors to membrane-protein structural study for decades. However, membrane proteins solubilized in conventional detergents tend to aggregate or denature over time. Stability of large eukaryotic membrane proteins with complex structures tends to be particularly poor, necessitating development of novel detergents with improved properties. Here, we prepared a novel class of detergents, designated 3,4-bis(hydroxymethyl)hexane-1,6-diol-based maltosides (HDMs). When tested on three membrane proteins, including two G-protein-coupled receptors (GPCRs), the new detergents displayed significantly better behaviors compared with DDM. Moreover, the HDMs were superior or comparable to LMNG, an amphiphile widely used for GPCR structural study. An optimal balance of detergent rigidity vs. flexibility of the HDMs is likely responsible for their favorable behaviors toward membrane-protein stability. Thus, the current study not only introduces the HDMs, with significant potential for membrane-protein structural study, but also suggests a useful guideline for designing novel detergents for membrane-protein research.

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Single-particle cryo-electron microscopy (cryo-EM) is a technique for biomolecular structure reconstruction from vitrified samples containing many copies of a biomolecular complex (known as single particles) at random unknown 3D orientations and positions. Cryo-EM allows reconstructing multiple conformations of the complexes from images of the same sample, which usually requires many rounds of 2D and 3D classifications to disentangle and interpret the combined conformational, orientational, and translational heterogeneity. The elucidation of different conformations is the key to understand molecular mechanisms behind the biological functions of the complexes and the key to novel drug discovery. Continuous conformational heterogeneity, due to gradual conformational transitions giving raise to many intermediate conformational states of the complexes, is both an obstacle for high-resolution 3D reconstruction of the conformational states and an opportunity to obtain information about multiple coexisting conformational states at once. HEMNMA method, specifically developed for analyzing continuous conformational heterogeneity in cryo-EM, determines the conformation, orientation, and position of the complex in each single particle image by image analysis using normal modes (the motion directions simulated for a given atomic structure or EM map), which in turn allows determining the full conformational space of the complex but at the price of high computational cost. In this article, we present a new method, referred to as DeepHEMNMA, which speeds up HEMNMA by combining it with a residual neural network (ResNet) based deep learning approach. The performance of DeepHEMNMA is shown using synthetic and experimental single particle images.

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A novel coagulation factor X (FX) Tyr319Cys mutation (Y99C as chymotrypsin numbering) was identified in a patient with severe bleeding. Unlike the earlier reported Y99A mutant, this mutant can bind and cleave its specific chromogenetic substrate at a normal level, suggesting an intact binding pocket. Here, using molecular dynamics simulations and MM-PBSA calculations on a FX-rivaroxaban (RIV) complex, we confirmed a much stronger binding of RIV in Y99C than in Y99A on a molecular level, which is actually the average result of multiple binding poses in dynamics. Detailed structural analyses also indicated the moderate flexibility of the 99-loop and the importance of the flexible side chain of Trp215 in the different binding poses. This case again emphasizes that binding of ligands may not only be a dynamic process but also a dynamic state, which is often neglected in drug design and screening based on static X-ray structures. In addition, the computational results somewhat confirmed our hypothesis on the activated Tyr319Cys FX (Y99C FXa) with an impaired procoagulant function to bind inhibitors of FXa and to be developed into a potential reversal agent for novel oral anticoagulants (NOAC).

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This study applies the 'Flexible-Acceptor' variant of the General Solubility Equation, GSE(Φ,B), to the prediction of the aqueous intrinsic solubility, log10 S 0, of FDA recently-approved (2016-2020) 'small-molecule' new molecular entities (NMEs). The novel equation had been shown to predict the solubility of drugs beyond Lipinski's 'Rule of 5' chemical space (bRo5) to a precision nearly matching that of the Random Forest Regression (RFR) machine learning method. Since then, it was found that the GSE(Φ,B) appears to work well not only for bRo5 NMEs, but also for Ro5 drugs. To put context to GSE(Φ,B), Yalkowsky's GSE(classic), Abraham's ABSOLV, and Breiman's RFR models were also applied to predict log10 S 0 of 72 newly-approve NMEs, for which useable reported solubility values could be accessed (nearly 60% from FDA New Drug Application published reports). Except for GSE (classic), the prediction models were retrained with an enlarged version of the Wiki-pS 0 database (nearly 400 added log10 S 0 entries since our recent previous study). Thus, these four models were further validated by the additional independent solubility measurements which the newly-approved drugs introduced. The prediction methods ranked RFR ~ GSE (Φ,B) > ABSOLV > GSE (classic) in performance. It was further demonstrated that the biases generated in the four separate models could be nearly eliminated in a consensus model based on the average of just two of the methods: GSE (Φ,B) and ABSOLV. The resulting consensus prediction equation is simple in form and can be easily incorporated into spreadsheet calculations. Even more significant, it slightly outperformed the RFR method.

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Antibody therapies are typically based on high-concentration formulations that need to be administered subcutaneously. These conditions induce several challenges, inter alia a viscosity suitable for injection, sufficient solution stability, and preservation of molecular function. To obtain systematic insights into the molecular factors, we study the dynamics on the molecular level under strongly varying solution conditions. In particular, we use solutions of antibodies with poly(ethylene glycol), in which simple cooling from room temperature to freezing temperatures induces a transition from a well-dispersed solution into a phase-separated and macroscopically arrested system. Using quasi-elastic neutron scattering during in situ cooling ramps and in prethermalized measurements, we observe a strong decrease in antibody diffusion, while internal flexibility persists to a significant degree, thus ensuring the movement necessary for the preservation of molecular function. These results are relevant for a more dynamic understanding of antibodies in high-concentration formulations, which affects the formation of transient clusters governing the solution viscosity.

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The latest coronavirus SARS-CoV-2, which causes coronavirus disease 2019 (COVID-19) pneumonia leading to the pandemic, contains 29 proteins. Among them, nucleocapsid protein (NCoV2) is one of the abundant proteins and shows multiple functions including packaging the RNA genome during the infection cycle. It has also emerged as a potential drug target. In this review, the current status of the research of NCoV2 is described in terms of molecular structure and dynamics. NCoV2 consists of two domains, i.e., the N-terminal domain (NTD) and the C-terminal domain (CTD) with a disordered region between them. Recent simulation studies have identified several potential drugs that can bind to NTD or CTD with high affinity. Moreover, it was shown that the degree of flexibility in the disordered region has a large effect on drug binding rate, suggesting the importance of molecular flexibility for the NCoV2 function. Molecular flexibility has also been shown to be integral to the formation of droplets, where NCoV2, RNA and/or other viral proteins gather through liquid-liquid phase separation and considered important for viral replication. Finally, as one of the future research directions, a strategy for obtaining the structural and dynamical information on the proteins contained in droplets is presented.

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Ribosome recycling is the final step of the cyclic process of translation, where the post-termination complex (PoTC) is disassembled by the concerted action of ribosome recycling factor (RRF) and elongation factor G (EF-G) in the sub-second time range. Since, however, both the RRF and PoTC display highly dynamic action during this process, it is difficult to assess the molecular details of the interactions between the factors and the ribosome that are essential for rapid subunit separation. Here we characterized the molecular dynamics of RRF and PoTC by combined use of molecular dynamics simulations, single molecule fluorescence detection and single-particle cryo-EM analysis, with time resolutions in the sub-millisecond to minute range. We found that RRF displays two-layer dynamics: intra- and inter-molecular dynamics during ribosome splitting. The intra-molecular dynamics exhibits two different configurations of RRF: 'bent' and 'extended'. A single-site mutant of RRF increases its propensity to the 'extended' conformation and leads to a higher binding affinity of RRF to the PoTC. The inter-molecular dynamics between RRF and EF-G in the PoTC reveals that the domain IV of EF-G pushes against the domain II of RRF, triggering the disruption of the major inter-subunit bridge B2a, and catalyzes the splitting.

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At present, the structure-activity relationships of soy protein isolate are still not well understood. In this paper, the relationship between molecular flexibility and emulsifying properties of soy protein isolate and soy protein isolate-glucose conjugates were investigated. The Maillard reaction was carried out at different temperature conditions (50 °C, 60 °C, 70 °C, 80 °C, and 90 °C) under a specific wet condition. Meanwhile, structural properties including surface hydrophobicity ( H0), molecular flexibility and secondary, tertiary, quaternary structures, and the free sulfhydryl group ( -SH) content were measured. The results showed that there was a good correlation between molecular flexibility and emulsifying properties, and the correlation coefficients was 0.920 ( P < 0.01) for emulsifying activity and 0.952 ( P < 0.01) for emulsion stability. Compared with soy protein isolate, the H0 of samples at different temperatures first increased and then decreased reaching a maximum at 70 °C, a red shift occurred during the whole given reaction conditions shown by the intrinsic fluorescence spectrum, and the free sulfhydryl content also displayed a marked increase ( P < 0.05). At the same time, the particle size gradually became smaller as the degree of grafting increased. The contents of ß-turn and random coil increased at the cost of α-helix and ß-sheet contents, as evidenced by Fourier transform infrared results. The findings could provide a deep insight into the structure-function relationship of soy protein isolate-glucose conjugates, thus providing theoretical guidance for further research of soy proteins.

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Docking simulations help us understand molecular interactions. Here we present a hands-on tutorial to utilize FlexAID (Flexible Artificial Intelligence Docking), an open source molecular docking software between ligands such as small molecules or peptides and macromolecules such as proteins and nucleic acids. The tutorial uses the NRGsuite PyMOL plugin graphical user interface to set up and visualize docking simulations in real time as well as detect and refine target cavities. The ease of use of FlexAID and the NRGsuite combined with its superior performance relative to widely used docking software provides nonexperts with an important tool to understand molecular interactions with direct applications in structure-based drug design and virtual high-throughput screening.

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The karyopherin family of nuclear transport receptors is composed of a long array of amphiphilic α-helices and undergoes flexible conformational changes to pass through the hydrophobic crowding barrier of the nuclear pore. Here, we focused on the characteristic enrichment of prolines in the middle of the outer α-helices of importin-ß. When these prolines were substituted with alanine, nuclear transport activity was reduced drastically in vivo and in vitro, and caused a severe defect in mitotic progression. These mutations did not alter the overall folding of the helical repeat or affect its interaction with cargo or the regulatory factor Ran. However, in vitro and in silico analyses revealed that the mutant lost structural flexibility and could not undergo rapid conformational changes when transferring from a hydrophilic to hydrophobic environment or vice versa. These findings reveal the essential roles of prolines in ensuring the structural flexibility and functional integrity of karyopherins.

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For the first time, the photoisomerization of a diarylethene moiety (DAET) in peptide conjugates was used to probe the effects of molecular rigidity/flexibility on the structure and behavior of model peptides bound to lipid membranes. The DAET unit was incorporated into the backbones of linear peptide-based constructs, connecting two amphipathic sequences (derived from the ß-stranded peptide (KIGAKI)3 and/or the α-helical peptide BP100). A ß-strand-DAET-α-helix and an α-helix-DAET-α-helix models were synthesized and studied in phospholipid membranes. Light-induced photoisomerization of the linker allowed the generation of two forms of each conjugate, which differed in the conformational mobility of the junction between the α-helical and/or the ß-stranded part of these peptidomimetic molecules. A detailed study of their structural, orientational and conformational behavior, both in isotropic solution and in phospholipid model membranes, was carried out using circular dichroism and solid-state 19F-NMR spectroscopy. The study showed that the rigid and flexible forms of the two conjugates had appreciably different structures only when embedded in an anisotropic lipid environment and only in the gel phase. The influence of the rigidity/flexibility of the studied conjugates on the lipid thermotropic phase transition was also investigated by differential scanning calorimetry. Both models were found to destabilize the lamellar gel phases.

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A historical challenge: Gas-phase electron diffraction and single-crystal X-ray diffraction are both established techniques, but they were both pushed to their limits by the challenge posed by the highly flexible tetranitromethane molecule. New approaches had to be developed for the structure of the molecule to be elucidated.

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During production, purification, formulation, and storage proteins for pharmaceutical or biotechnological applications face solution conditions that are unfavorable for their stability. Such harmful conditions include extreme pH changes, high ionic strengths or elevated temperatures. The characterization of the main influencing factors promoting undesired changes of protein conformation and aggregation, as well as the manipulation and selective control of protein stabilities are crucially important to biopharmaceutical research and process development. In this context PEGylation, i.e. the covalent attachment of polyethylene glycol (PEG) to proteins, represents a valuable strategy to improve the physico-chemical properties of proteins. In this work, the influence of PEG molecular weight and PEGylation degree on the physical stability of PEGylated lysozyme is investigated. Specifically, conformational and colloidal properties were studied by means of high-throughput melting point determination and automated generation of protein phase diagrams, respectively. Lysozyme from chicken egg-white as a model protein was randomly conjugated to 2kDa, 5kDa and 10kDa mPEG-aldehyde and resulting PEGamer species were purified by chromatographic separation. Besides protein stability assessment, residual enzyme activities were evaluated employing a Micrococcus lysodeikticus based activity assay. PEG molecules with lower molecular weights and lower PEGylation degrees resulted in higher residual activities. Changes in enzyme activities upon PEGylation have shown to result from a combination of steric hindrance and molecular flexibility. In contrast, higher PEG molecular weights and PEGylation degrees enhanced conformational and colloidal stability. By PEGylating lysozyme an increase of the protein solubility by more than 11-fold was achieved.

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Due to widespread exposure of human being to various sources of static magnetic fields (SMF), their effect on the spatial and temporal status of structure, arrangement, and polymerization of tubulin was studied at the molecular level. The intrinsic fluorescence intensity of tubulin was increased by SMF, indicating the repositioning of tryptophan and tyrosine residues. Circular Dichroism spectroscopy revealed variations in the ratios of alpha helix, beta, and random coil structures of tubulin as a result of exposure to SMF at 100, 200, and 300 mT. Transmission Electron microscopy of microtubules showed breaches and curvatures whose risk of occurrence increased as a function of field strength. Dynamic light scattering revealed an increase in the surface potential of tubulin aggregates exposed to SMF. The rate and extent of polymerization increased by 9.8 and 33.8%, at 100 and 300 mT, respectively, but decreased by 36.16% at 200 mT. The conductivity of polymerized tubulin increased in the presence of 100 and 300 mT SMF but remained the same as the control at 200 mT. The analysis of flexible amino acids along the sequence of tubulin revealed higher SMF susceptibility in the helical electron conduction pathway set through histidines rather than the vertical electron conduction pathway formed by tryptophan residues. The results reveal structural and functional effects of SMF on tubulin assemblies and microtubules that can be considered as a potential means to address the safety issues and for manipulation of bioelectrical characteristics of cytosol, intracellular trafficking and thus, the living status of cells, remotely.

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Sugars are often used as stabilizers of protein formulations during freeze-drying. However, not all sugars are equally suitable for this purpose. Using in-line near-infrared spectroscopy during freeze-drying, it is shown here that hydrogen bond formation during freeze-drying, under secondary drying conditions in particular, can be related to the preservation of the functionality and structure of proteins during storage. The disaccharide trehalose was best capable of forming hydrogen bonds with the model protein, lactate dehydrogenase, thereby stabilizing it, followed by the molecularly flexible oligosaccharide inulin 4kDa. The molecularly rigid oligo- and polysaccharides dextran 5kDa and 70kDa, respectively, formed the least amount of hydrogen bonds and provided least stabilization of the protein. It is concluded that smaller and molecularly more flexible sugars are less affected by steric hindrance, allowing them to form more hydrogen bonds with the protein, thereby stabilizing it better.

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