From covalent transition states in chemistry to noncovalent in biology: from ß- to Φ-value analysis of protein folding.

Solving the mechanism of a chemical reaction requires determining the structures of all the ground states on the pathway and the elusive transition states linking them. 2024 is the centenary of Brønsted's landmark paper that introduced the ß-value and structure-activity studies as the only experimental means to infer the structures of transition states. It involves making systematic small changes in the covalent structure of the reactants and analysing changes in activation and equilibrium-free energies. Protein engineering was introduced for an analogous procedure, Φ-value analysis, to analyse the noncovalent interactions in proteins central to biological chemistry. The methodology was developed first by analysing noncovalent interactions in transition states in enzyme catalysis. The mature procedure was then applied to study transition states in the pathway of protein folding - 'part (b) of the protein folding problem'. This review describes the development of Φ-value analysis of transition states and compares and contrasts the interpretation of ß- and Φ-values and their limitations. Φ-analysis afforded the first description of transition states in protein folding at the level of individual residues. It revealed the nucleation-condensation folding mechanism of protein domains with the transition state as an expanded, distorted native structure, containing little fully formed secondary structure but many weak tertiary interactions. A spectrum of transition states with various degrees of structural polarisation was then uncovered that spanned from nucleation-condensation to the framework mechanism of fully formed secondary structure. Φ-analysis revealed how movement of the expanded transition state on an energy landscape accommodates the transition from framework to nucleation-condensation mechanisms with a malleability of structure as a unifying feature of folding mechanisms. Such movement follows the rubric of analysis of classical covalent chemical mechanisms that began with Brønsted. Φ-values are used to benchmark computer simulation, and Φ and simulation combine to describe folding pathways at atomic resolution.

A promising approach for the removal of hexavalent and trivalent chromium from aqueous solution using low-cost biomaterial.

Heavy metal pollution is an enduring environmental challenge that calls for sustainable and eco-friendly solutions. One promising approach is to harness discarded plant biomass as a highly efficient environmental friendly adsorbents. In this context, a noteworthy study has spotlighted the employment of Euryale ferox Salisbury seed coat (E.feroxSC) for the exclusion of trivalent and hexavalent chromium ions. This study aims to transform discarded plant residue into a novel, environmentally friendly, and cost-effective alternative adsorbent, offering a compelling alternative to more expensive adsorption methods. By repurposing natural materials, we can contribute to mitigating heavy-metal pollution while promoting sustainable and economically viable solutions in environmental remediation. The effect of different parameters, i.e., chromium ions' initial concentration (5-25 mg L-1), solution pH (2-7), adsorbent dosage (0.2-2.4 g L-1), contact time (20-240 min), and temperature (298-313 K), were investigated. E.feroxSC proved highly effective, achieving 96.5% removal of Cr(III) ions at pH 6 and 97.7% removal of Cr(VI) ions at pH 2, with a maximum biosorption capacity of 18.33 mg/g for Cr(III) and 13.64 mg/g for Cr(VI), making it a promising, eco-friendly adsorbent for tackling heavy-metal pollution. The adsorption process followed the pseudo-second-order kinetic model, aligning well with the Langmuir isotherm, exhibited favorable thermodynamics, and was characterized as feasible, spontaneous, and endothermic with physisorption mechanisms. The investigation revealed that E.feroxSC effectively adsorbed Cr(VI) which could be rejuvenated in a basic solution with minimal depletion in its adsorption capacity. Conversely, E.feroxSC's adsorption of Cr(III) demanded rejuvenation in an acidic milieu, exhibiting comparatively less efficient restoration.

Novel mint-stalks derived biochar for the adsorption of methylene blue dye: Effect of operating parameters, adsorption mechanism, kinetics, isotherms, and thermodynamics.

The pyrolysis of mint stalks and lemon peels was performed to synthesize mint-stalks (MBC) and lemon-peels (LBC) derived biochars for adsorbing methylene blue (MB). The preparation, characterization, and application of MBC in adsorption have not been reported in the literature. MBC showed higher surface area and carbon content than that of LBC. The removal ratios of MB were 87.5% and 60% within 90 min for MBC and LBC, respectively at pH 7, temperature of 30oC, adsorbent dose of 0.5 g/L, and MB concentration of 5 mg/L. The optimal MBC dose was 1 g/L achieving a removal efficiency of 93.6% at pH 7, temperature of 30oC, contact time of 90 min, and initial dye concentration of 5.0 mg/L. The adsorption efficiency decreased from 98.6% to 31.33% by raising the dye concentration from 3.0 mg/L to 30 mg/L. Further, the increase of adsorbent dose to 10 g/L could achieve 94.2%, 90.3%, 87.6%, and 84.1% removal efficiencies of MB in the case of initial concentrations of 200 mg/L, 300 mg/L, 400 mg/L, and 500 mg/L, respectively. MBC showed high stability in adsorbing MB under five cycles, and the performed analyses after adsorption reaffirmed the stability of MBC. The adsorption mechanism indicated that the adsorption of MB molecules on the biochar's surface was mainly because of the electrostatic interaction, hydrogen bonding, and π-π stacking. Pseudo-second-order and Langmuir models could efficiently describe the adsorption of MB on the prepared biochar. The adsorption process is endothermic and spontaneous based on the adsorption thermodynamics. The proposed adsorption system is promising and can be implemented on a bigger scale. Moreover, the prepared biochar can be implemented in other applications such as photocatalysis, periodate, and persulfate activation-based advanced oxidation processes.

Pyrolysis of Euphorbia Rigida: A study on thermal characterizations, kinetics, thermodynamics via TG-FTIR analysis.

Euphorbia Rigida (E. Rigida), a lignocellulosic biomass with low ash content, is a suitable feedstock for pyrolysis. This work investigated the physicochemical characteristics and thermokinetic analysis of E. Rigida pyrolysis by using isoconversional and master plots methods. Ultimate and proximate analyses and oxygen bomb calorimeter were used to determine the physicochemical parameters. The activation energies were calculated using model-free methods (KAS, Friedman and Starink) and were found as 184, 178 and 185 kJ/mol, respectively. Using Fraser-Suzuki deconvolution, pseudo-components were also calculated and the active pyrolysis region was divided into three zones. The master plots showed that reaction order mechanisms (Fn) were effective in Zone I, and diffusion mechanisms (Dn) were well matched in Zone II and Zone III. The thermodynamic parameters (ΔH, ΔG and ΔS) were calculated and according to these results, E. Rigida pyrolysis was an endothermic and non-spontaneous process.

Structure, Self-Assembly, and Phase Behavior of Neuroactive N-Acyl GABAs: Doxorubicin Encapsulation in NPGABA/DPPC Liposomes and Release Studies.

N-Acylated amino acids and neurotransmitters in mammals exert significant biological effects on the nervous system, immune responses, and vasculature. N-Acyl derivatives of γ-aminobutyric acid (N-acyl GABA), which belong to both classes mentioned above, are prominent among them. In this work, a homologous series of N-acyl GABAs bearing saturated N-acyl chains (C8-C18) have been synthesized and characterized with respect to self-assembly, thermotropic phase behavior, and supramolecular organization. Differential scanning calorimetric studies revealed that the transition enthalpies and entropies of N-acyl GABAs are linearly dependent on the acyl chain length. The crystal structure of N-tridecanoyl GABA showed that the molecules are packed in bilayers with the acyl chains aligned parallel to the bilayer normal and that the carboxyl groups from opposite layers associate to form dimeric structures involving strong O-H···O hydrogen bonds. In addition, N-H···O and C-H···O hydrogen bonds between amide moieties of adjacent molecules within each layer stabilize the molecular packing. Powder X-ray diffraction studies showed odd-even alternation in the d spacings, suggesting that the odd chain and even chain compounds pack differently. Equimolar mixtures of N-palmitoyl GABA and dipalmitoylphosphatidylcholine (DPPC) were found to form stable unilamellar vesicles with diameters of ∼300-340 nm, which could encapsulate doxorubicin, an anticancer drug, with higher efficiency and better release characteristics than DPPC liposomes at physiologically relevant pH. These liposomes exhibit faster release of doxorubicin at acidic pH (<7.0), indicating their potential utility as drug carriers in cancer chemotherapy.

G-Quadruplexes as Sensors of Intracellular Na+/K+ Ratio: Potential Role in Regulation of Transcription and Translation.

Data on the structure of G-quadruplexes, noncanonical nucleic acid forms, supporting an idea of their potential participation in regulation of gene expression in response to the change in intracellular Na+i/K+i ratio are considered in the review. Structural variety of G-quadruplexes, role of monovalent cations in formation of this structure, and thermodynamic stability of G-quadruplexes are described. Data on the methods of their identification in the cells and biological functions of these structures are presented. Analysis of information about specific interactions of G-quadruplexes with some proteins was conducted, and their potential participation in the development of some pathological conditions, in particular, cancer and neurodegenerative diseases, is considered. Special attention is given to the plausible role of G-quadruplexes as sensors of intracellular Na+i/K+i ratio, because alteration of this parameter affects folding of G-quadruplexes changing their stability and, thereby, organization of the regulatory elements of nucleic acids. The data presented in the conclusion section demonstrate significant change in the expression of some early response genes under certain physiological conditions of cells and tissues depending on the intracellular Na+i/K+i ratio.

[Effects of maltodextrin on water adsorption and thermodynamic properties of Codonopsis Radix spray-dried powder].

This study aims to reveal the effects of maltodextrin(MD) on the water adsorption and thermodynamic properties of Codonopsis Radix(DS) spray-dried powder by determining the moisture and energy changes of the powder in the process of moisture absorption. The static weighing method was used to obtain the isothermal water adsorption data of the spray-dried powder in 6 saturated salt solutions(KAc, MgCl_2·6H_2O, K_2CO_3, NaBr, NaCl, and KCl) at 3 temperatures(25, 35, and 45 ℃). Six models were used for fitting of the water adsorption process, and the most suitable model was selected based on the model performance. Furthermore, the corresponding net equivalent adsorption heat and differential entropy were calculated, and the adsorption entropy change was integrated. The linear relationship between net equivalent adsorption heat and differential entropy was drawn based on the entropy-enthalpy complementarity theory. The results showed that the water adsorption properties of DS and DS-MD spray-dried powder followed the type Ⅲ isotherm and was well fitted by the GAB model. The monolayer water content M_0 decreased with the increase in temperature. At the same temperature, the M_0 of DS spray-dried powder decreased after the addition of MD. The net equivalent adsorption heat and differential entropy of DS and DS-MD spray-dried powder decreased with the increase in water content, which presented a linear relationship. The addition of MD decreased the water activity corresponding to the lowest integral adsorption entropy of the powder, and the system became more stable. The results indicated that the spray-dried powder became more stable after the addition of MD.

Removal of antiretroviral drugs from wastewater using activated macadamia nutshells: Adsorption kinetics, adsorption isotherms, and thermodynamic studies.

Antiretroviral drugs (ARVDs) have been extensively employed in health care to improve the quality of life and lifecycle longevity. However, overuse and improper disposal of ARVDs have been recognized as an emerging concern whereby wastewater treatment major recipients. Therefore, in this work, the activated macadamia nutshells (MCNs) were explored as low-cost adsorbents for the removal of ARVDs in wastewater samples. Fourier transform infrared spectroscopy (FTIR), Scanning Electron microscopy (SEM), Brunauer-Emmet-Teller (BET), and Powder X-ray diffraction (PXRD). The highest removal efficiency (R.E) was above 86% for the selected analytes nevirapine, abacavir, and efavirenz. The maximum adsorption capacity of the functionalized MCN adsorbent was 10.79, 27.44, and 38.17 mg/g for nevirapine, abacavir, and efavirenz for HCl-modified adsorbent. In contrast, NaOH modified had adsorption capacities of 13.67, 14.25, and 20.79 mg/g. The FTIR showed distinct functional groups OH and CO, which facilitate the removal of selected ARVDs. From studying kinetics parameters, the pseudo-second-order (R2 = 0.990-0.996) was more dominant than the pseudo-first-order (R2 = 0.872-0.994). The experimental data was most fitted in the Freundlich model with (R2 close to 1). The thermodynamic parameters indicated that the adsorption process was spontaneous and exothermic. The study indicated that MCNs are an eco-friendly, low-cost, and effective adsorbent for the removal of nevirapine, abacavir, and efavirenz. PRACTITIONER POINTS: Modification macadamia nutshell with HCl and NaOH improved physio-chemical properties that yielded high removal efficiency compared with raw macadamia nutshells. Modification of macadamia by HCl showed high removal efficiency, which could be attributed to high interaction such as H-bonding that improves adsorption. The macadamia nutshell as an adsorbent showed so much robustness with regeneration studies yielding to about 69.64% of selected compounds.

Uranium capture from aqueous solution using palm-waste based activated carbon: sorption kinetics and equilibrium.

Carbonaceous materials produced from agricultural waste (palm kernel shell) by pyrolysis can be a proper type of low-cost adsorbent for wide uses in radioactive effluent treatment. In this context, the as-produced bio-char (labeled as PBC) and its sub-driven sulfuric acid and zinc oxide activated carbons (labeled as PBC-SA, and PBC-Zn respectively) were employed as adsorbents for uranium sorption from aqueous solution. Various analytical techniques, including SEM (Scanning Electron Microscopy), EXD (X-ray Diffraction), BET (Brunauer-Emmett-Teller), FTIR (Fourier Transform Infrared Spectroscopy), and Zeta potential, provide insights into the material characteristics. Kinetic and isotherm investigations illuminated that the sorption process using the three sorbents is nicely fitted with Pseudo-second-order-kinetic and Langmuir isotherm models. The picked data display that the equilibrium time was 60 min, and the maximum sorption capacity was 9.89, 16.8, and 21.9 mg/g for PBC, PBC-SA, and PBC-Zn respectively, which reflects the highest affinity for zinc oxide, activated bio-char, among the three adsorbents, for uranium taking out from radioactive wastewater. Sorption thermodynamics declare that the sorption of U(VI) is an exothermic, spontaneous, and feasible process. About 92% of the uranium-loaded PBC-Zn sorbent was eluted using 1.0 M CH3COONa sodium ethanoate solution, and the sorbent demonstrated proper stability for 5 consecutive sorption/desorption cycles.

Revealing the Interaction Mechanism between Mycobacterium tuberculosis GyrB and Novobiocin, SPR719 through Binding Thermodynamics and Dissociation Kinetics Analysis.

With the rapid emergence of drug-resistant strains of Mycobacterium tuberculosis (Mtb), various levels of resistance against existing anti-tuberculosis (TB) drugs have developed. Consequently, the identification of new anti-TB targets and drugs is critically urgent. DNA gyrase subunit B (GyrB) has been identified as a potential anti-TB target, with novobiocin and SPR719 proposed as inhibitors targeting GyrB. Therefore, elucidating the molecular interactions between GyrB and its inhibitors is crucial for the discovery and design of efficient GyrB inhibitors for combating multidrug-resistant TB. In this study, we revealed the detailed binding mechanisms and dissociation processes of the representative inhibitors, novobiocin and SPR719, with GyrB using classical molecular dynamics (MD) simulations, tau-random acceleration molecular dynamics (τ-RAMD) simulations, and steered molecular dynamics (SMD) simulations. Our simulation results demonstrate that both electrostatic and van der Waals interactions contribute favorably to the inhibitors' binding to GyrB, with Asn52, Asp79, Arg82, Lys108, Tyr114, and Arg141 being key residues for the inhibitors' attachment to GyrB. The τ-RAMD simulations indicate that the inhibitors primarily dissociate from the ATP channel. The SMD simulation results reveal that both inhibitors follow a similar dissociation mechanism, requiring the overcoming of hydrophobic interactions and hydrogen bonding interactions formed with the ATP active site. The binding and dissociation mechanisms of GyrB with inhibitors novobiocin and SPR719 obtained in our work will provide new insights for the development of promising GyrB inhibitors.

Break oily water emulsion during petroleum enhancing production processes using green approach for the synthesis of SnCuO@FeO nanocomposite from microorganisms.

The aim of this work was to synthesize a green nanoparticle SnCuO@FeO nanocomposite core-shell to break oily water emulsions during petroleum-enhancing production processes as an alternative to chemical and physical processes. In this study, eight bacterial isolates (MHB1-MHB8) have been isolated from tree leaves, giant reeds, and soil samples. The investigation involved testing bacterial isolates for their ability to make FeO nanoparticles and choosing the best producers. The selected isolate (MHB5) was identified by amplification and sequencing of the 16S rRNA gene as Bacillus paramycoides strain OQ878685. MHB5 produced the FeO nanoparticles with the smallest particle size (78.7 nm) using DLS. XRD, FTIR, and TEM were used to characterize the biosynthesized nanoparticles. The jar experiment used SnCuO@FeO with different ratios of Sn to CuO (1:1, 2:1, and 3:1) to study the effect of oil concentration, retention time, and temperature. The most effective performance was observed with a 1:1 ratio of Sn to CuO, achieving an 85% separation efficiency at a concentration of 5 mg/L, for a duration of 5 min, and at a temperature of 373 K. Analysis using kinetic models indicates that the adsorption process can be accurately described by both the pseudo-first-order and pseudo-second-order models. This suggests that the adsorption mechanism likely involves a combination of film diffusion and intraparticle diffusion. Regarding the adsorption isotherm, the Langmuir model provides a strong fit for the data, while the D-R model indicates that physical interactions primarily govern the adsorption mechanism. Thermodynamic analysis reveals a ∆H value of 18.62 kJ/mol, indicating an exothermic adsorption process. This suggests that the adsorption is a favorable process, as energy is released during the process. Finally, the synthesized green SnCuO@FeO nanocomposite has potential for use in advanced applications in the oil and gas industry to help the industry meet regulatory compliance, lower operation costs, reduce environmental impact, and enhance production efficiency.

The influence of model building schemes and molecular dynamics sampling on QM-cluster models: the chorismate mutase case study.

Most QM-cluster models of enzymes are constructed based on X-ray crystal structures, which limits comparison to in vivo structure and mechanism. The active site of chorismate mutase from Bacillus subtilis and the enzymatic transformation of chorismate to prephenate is used as a case study to guide construction of QM-cluster models built first from the X-ray crystal structure, then from molecular dynamics (MD) simulation snapshots. The Residue Interaction Network ResidUe Selector (RINRUS) software toolkit, developed by our group to simplify and automate the construction of QM-cluster models, is expanded to handle MD to QM-cluster model workflows. Several options, some employing novel topological clustering from residue interaction network (RIN) information, are evaluated for generating conformational clustering from MD simulation. RINRUS then generates a statistical thermodynamic framework for QM-cluster modeling of the chorismate mutase mechanism via refining 250 MD frames with density functional theory (DFT). The 250 QM-cluster models sampled provide a mean ΔG‡ of 10.3 ± 2.6 kcal mol-1 compared to the experimental value of 15.4 kcal mol-1 at 25 °C. While the difference between theory and experiment is consequential, the level of theory used is modest and therefore "chemical" accuracy is unexpected. More important are the comparisons made between QM-cluster models designed from the X-ray crystal structure versus those from MD frames. The large variations in kinetic and thermodynamic properties arise from geometric changes in the ensemble of QM-cluster models, rather from the composition of the QM-cluster models or from the active site-solvent interface. The findings open the way for further quantitative and reproducible calibration in the field of computational enzymology using the model construction framework afforded with the RINRUS software toolkit.

Thermodynamic and molecular dynamic insights into how fusion influences peptide-tag recognition of an antibody.

To understand the effect of protein fusion on the recognition of a peptide-tag by an antibody, we fused a CCR5-derived peptide-tag (pep1) to GFP and investigated its recognition by an anti-pep1 antibody, 4B08. First, to characterize the thermodynamic properties associated with the pep1-4B08 binding, isothermal titration calorimetry experiments were conducted. It was found that pep1 fused to the C-terminus of GFP (GFP-CT) enhanced the enthalpic gain by 2.1 kcal mol-1 and the entropic loss only by 0.9 kcal mol-1, resulting in an 8-fold increase in the binding affinity compared to the unfused pep1. On the other hand, pep1 fused to the N-terminus of GFP (GFP-NT) enhanced the enthalpic gain by 3.0 kcal mol-1 and the entropic loss by 3.2 kcal mol-1, leading to no significant enhancement of the binding affinity. To gain deeper insights, molecular dynamics simulations of GFP-NT, GFP-CT, and pep1 were performed. The results showed that the location of the fusion point sensitively affects the interaction energy, the solvent accessible surface area, and the fluctuation of pep1 in the unbound state, which explains the difference in the experimental thermodynamic properties.

Modeling Zinc Complexes Using Neural Networks.

Understanding the energetic landscapes of large molecules is necessary for the study of chemical and biological systems. Recently, deep learning has greatly accelerated the development of models based on quantum chemistry, making it possible to build potential energy surfaces and explore chemical space. However, most of this work has focused on organic molecules due to the simplicity of their electronic structures as well as the availability of data sets. In this work, we build a deep learning architecture to model the energetics of zinc organometallic complexes. To achieve this, we have compiled a configurationally and conformationally diverse data set of zinc complexes using metadynamics to overcome the limitations of traditional sampling methods. In terms of the neural network potentials, our results indicate that for zinc complexes, partial charges play an important role in modeling the long-range interactions with a neural network. Our developed model outperforms semiempirical methods in predicting the relative energy of zinc conformers, yielding a mean absolute error (MAE) of 1.32 kcal/mol with reference to the double-hybrid PWPB95 method.

Understanding the Reversible Binding of a Multichain Protein-Protein Complex through Free-Energy Calculations.

We demonstrate that the binding affinity of a multichain protein-protein complex, insulin dimer, can be accurately predicted using a streamlined route of standard binding free-energy calculations. We find that chains A and C, which do not interact directly during binding, stabilize the insulin monomer structures and reduce the binding affinity of the two monomers, therefore enabling their reversible association. Notably, we confirm that although classical methods can estimate the binding affinity of the insulin dimer, conventional molecular dynamics, enhanced sampling algorithms, and classical geometrical routes of binding free-energy calculations may not fully capture certain aspects of the role played by the noninteracting chains in the binding dynamics. Therefore, this study not only elucidates the role of noninteracting chains in the reversible binding of the insulin dimer but also offers a methodological guide for investigating the reversible binding of multichain protein-protein complexes utilizing streamlined free-energy calculations.

Design and analysis of self-priming extension DNA hairpin probe for miRNA detection based on a unified dynamic programming framework.

MicroRNAs (miRNAs) are potential biomarkers for cancer diagnosis and prognosis, methods for detecting miRNAs with high sensitivity, selectivity, and stability are urgently needed. Various nucleic acid probes that have traditionally been for this purpose suffer several drawbacks, including inefficient signal-to-noise ratios and intensities, high cost, and time-consuming method establishment. Computing tools used for investigating the thermodynamics of DNA hybridization reactions can accurately predict the secondary structure of DNA and the interactions between DNA molecules. Herein, NUPACK was used to design a series of nucleic acid probes and develop a phosphorothioated-terminal hairpin formation and self-priming extension (PS-THSP) signal amplification strategy, which enabled the ultrasensitive detection of miR-200a in serum samples. The free and binding energies of the DNA detection probes calculated using NUPACK, as well as the biological experimental results, were considered synthetically to select the best sequence and experimental conditions. A unified dynamic programming framework, NUPACK analysis and the experimental data, were complementary and improved the designed model in all respects. Our study demonstrates the feasibility of using computer technology such as NUPACK to simplify the experimental process and provide intuitive results.

Reversible strain-promoted DNA polymerization.

Molecular strain can be introduced to influence the outcome of chemical reactions. Once a thermodynamic product is formed, however, reversing the course of a strain-promoted reaction is challenging. Here, a reversible, strain-promoted polymerization in cyclic DNA is reported. The use of nonhybridizing, single-stranded spacers as short as a single nucleotide in length can promote DNA cyclization. Molecular strain is generated by duplexing the spacers, leading to ring opening and subsequent polymerization. Then, removal of the strain-generating duplexers triggers depolymerization and cyclic dimer recovery via enthalpy-driven cyclization and entropy-mediated ring contraction. This reversibility is retained even when a protein is conjugated to the DNA strands, and the architecture of the protein assemblies can be modulated between bivalent and polyvalent states. This work underscores the utility of using DNA not only as a programmable ligand for assembly but also as a route to access restorable bonds, thus providing a molecular basis for DNA-based materials with shape-memory, self-healing, and stimuli-responsive properties.

Gaussian accelerated molecular dynamics simulations facilitate prediction of the permeability of cyclic peptides.

Despite their widespread use as therapeutics, clinical development of small molecule drugs remains challenging. Among the many parameters that undergo optimization during the drug development process, increasing passive cell permeability (i.e., log(P)) can have some of the largest impact on potency. Cyclic peptides (CPs) have emerged as a viable alternative to small molecules, as they retain many of the advantages of small molecules (oral availability, target specificity) while being highly effective at traversing the plasma membrane. However, the relationship between the dominant conformations that typify CPs in an aqueous versus a membrane environment and cell permeability remain poorly characterized. In this study, we have used Gaussian accelerated molecular dynamics (GaMD) simulations to characterize the effect of solvent on the free energy landscape of lariat peptides, a subset of CPs that have recently shown potential for drug development (Kelly et al., JACS 2021). Differences in the free energy of lariat peptides as a function of solvent can be used to predict permeability of these molecules, and our results show that permeability is most greatly influenced by N-methylation and exposure to solvent. Our approach lays the groundwork for using GaMD as a way to virtually screen large libraries of CPs and drive forward development of CP-based therapeutics.

Helical Content Correlations and Hydration Structures of the Folding Ensemble of the B Domain of Protein A.

The B domain of protein A (BdpA), a small three-helix bundle, folds on a time scale of a few microseconds with heterogeneous native and unfolded states. It is widely used as a model for understanding protein folding mechanisms. In this work, we use structure-based models (SBMs) and atomistic simulations to comprehensively investigate how BdpA folding is associated with the formation of its secondary structure. The energy landscape visualization method (ELViM) was used to characterize the pathways that connect the folded and unfolded states of BdpA as well as the sets of structures displaying specific ellipticity patterns. We show that the native state conformational diversity is due mainly to the conformational variability of helix I. Helices I, II, and III occur in a weakly correlated manner, with Spearman's rank correlation coefficients of 0.1539 (I and II), 0.1259 (I and III), and 0.2561 (II and III). These results, therefore, suggest the highest cooperativity between helices II and III. Our results allow the clustering of partially folded structures of folding of the B domain of protein A on the basis of its secondary structure, paving the way to an understanding of environmental factors in the relative stability of the basins of the folding ensemble, which are illustrated by the structural dependency of the protein hydration structures, as computed with minimum-distance distribution functions.