The Fundamental Role of Flexibility on the Strength of Molecular Binding

Phospholipid-induced secondary structural changes of lysozyme polymorphic amyloid fibrils studied using vacuum-ultraviolet circular dichroism

The hallmark of amyloidosis, such as Alzheimer's disease and Parkinson's disease, is the deposition of amyloid fibrils in various internal organs. The onset of the disease is related to the strength of cytotoxicity caused by toxic amyloid species. Furthermore, amyloid fibrils show polymorphism, where some types of fibrils are cytotoxic while others are not. It is thus essential to understand the molecular mechanism of cytotoxicity, part of which is caused by the interaction between amyloid polymorphic fibrils and cell membranes. Here, using amyloid polymorphs of hen egg white lysozyme, which is associated with hereditary systemic amyloidosis, showing different levels of cytotoxicity and liposomes of DMPC and DMPG, changes in the secondary structure of the polymorphs and the structural state of phospholipid membranes caused by the interaction were investigated using vacuum-ultraviolet circular dichroism (VUVCD) and Laurdan fluorescence measurements, respectively. Analysis has shown that the more cytotoxic polymorph increases the antiparallel β-sheet content and causes more disorder in the membrane structure while the other less cytotoxic polymorph shows the opposite structural changes and causes less structural disorder in the membrane. These results suggest a close correlation between the structural properties of amyloid fibrils and the degree of structural disorder of phospholipid membranes, both of which are involved in the fundamental process leading to amyloid cytotoxicity.

Quantification of thermodynamic effects of carbohydrate multivalency on avidity using synthetic discrete glycooligomers

A quantitative understanding of thermodynamic effects of avidity in biomolecular interactions is important. Herein, we synthesized discrete glycooligomers and evaluated their interactions with a model protein using isothermal titration calorimetry. The dimeric glycooligomer exhibited higher binding constants compared to the glycomonomer, attributed to the reduced conformational entropy loss through local presentation of multiple carbohydrate units. Conversely, divalent glycoligands with polyethylene glycol linkers, aiming for multivalent binding, showed enhanced interactions through increased enthalpy. These findings emphasize the importance of distinguishing between the "local avidity" and the "multipoint avidity".

An In Silico Analysis of Genetic Variants and Structural Modeling of the Human Frataxin Protein in Friedreich's Ataxia

Friedreich's Ataxia (FRDA) stands out as the most prevalent form of hereditary ataxias, marked by progressive movement ataxia, loss of vibratory sensitivity, and skeletal deformities, severely affecting daily functioning. To date, the only medication available for treating FRDA is Omaveloxolone (Skyclarys®), recently approved by the FDA. Missense mutations within the human frataxin (FXN) gene, responsible for intracellular iron homeostasis regulation, are linked to FRDA development. These mutations induce FXN dysfunction, fostering mitochondrial iron accumulation and heightened oxidative stress, ultimately triggering neuronal cell death pathways. This study amalgamated 226 FXN genetic variants from the literature and database searches, with only 18 previously characterized. Predictive analyses revealed a notable prevalence of detrimental and destabilizing predictions for FXN mutations, predominantly impacting conserved residues crucial for protein function. Additionally, an accurate, comprehensive three-dimensional model of human FXN was constructed, serving as the basis for generating genetic variants I154F and W155R. These variants, selected for their severe clinical implications, underwent molecular dynamics (MD) simulations, unveiling flexibility and essential dynamic alterations in their N-terminal segments, encompassing FXN42, FXN56, and FXN78 domains pivotal for protein maturation. Thus, our findings indicate potential interaction profile disturbances in the FXN42, FXN56, and FXN78 domains induced by I154F and W155R mutations, aligning with the existing literature.

Adaptive lambda schemes for efficient relative binding free energy calculation

The relative free energy perturbation (RFEP) calculation is one of the most theoretically sound computational chemistry approaches for the binding affinity prediction. However, its application is often hindered by the complexity of the calculation choices and the requirement of expertise in the field. Improper lambda scheme of RFEP may result in deviations from an accurate description of the perturbation process and is prone to erroneous affinity predictions. To address such challenges, an automated adaptive lambda method is proposed where the adaptive lambda schemes are obtained through a split-and-merge algorithm based on the pilot runs. The newly established workflow along with a series of improvements to the perturbation settings increases the consistency of the RFEP calculation results. Comparing the pilot and adaptive lambda schemes, the latter demonstrated improvements in convergence and reproducibility and lowered the mean unsigned error and the root-mean-square error. Overall, the adaptive lambda method is a reliable and robust choice to predict small molecule relative binding free energy and can be capitalized to benefit routine RFEP calculations for drug discovery projects.

In Silico Analyses of a Promising Drug Candidate for the Treatment of Amyotrophic Lateral Sclerosis Targeting Superoxide Dismutase I Protein

Amyotrophic lateral sclerosis (ALS) is the most prevalent motor neuron disorder in adults, which is associated with a highly disabling condition. To date, ALS remains incurable, and the only drugs approved by the FDA for its treatment confer a limited survival benefit. Recently, SOD1 binding ligand 1 (SBL-1) was shown to inhibit in vitro the oxidation of a critical residue for SOD1 aggregation, which is a central event in ALS-related neurodegeneration. In this work, we investigated the interactions between SOD1 wild-type and its most frequent variants, i.e., A4V (NP_000445.1:p.Ala5Val) and D90A (NP_000445.1:p.Asp91Val), with SBL-1 using molecular dynamics (MD) simulations. The pharmacokinetics and toxicological profile of SBL-1 were also characterized in silico. The MD results suggest that the complex SOD1-SBL-1 remains relatively stable and interacts within a close distance during the simulations. This analysis also suggests that the mechanism of action proposed by SBL-1 and its binding affinity to SOD1 may be preserved upon mutations A4V and D90A. The pharmacokinetics and toxicological assessments suggest that SBL-1 has drug-likeness characteristics with low toxicity. Our findings, therefore, suggested that SBL-1 may be a promising strategy to treat ALS based on an unprecedented mechanism, including for patients with these frequent mutations.

Heating-mediated purification of active FGF21 and structure-based design of its variant with enhanced potency

Fibroblast growth factor 21 (FGF21) has pharmaceutical potential against obesity-related metabolic disorders, including non-alcoholic fatty liver disease. Since thermal stability is a desirable factor for therapeutic proteins, we investigated the thermal behavior of human FGF21. FGF21 remained soluble after heating; thus, we examined its temperature-induced structural changes using circular dichroism (CD). FGF21 showed inter-convertible temperature-specific CD spectra. The CD spectrum at 100 °C returned to that at 20 °C when the heated FGF21 solution was cooled. Through loop swapping, the connecting loop between β10 and β12 in FGF21 was revealed to be associated with the unique thermal behavior of FGF21. According to surface plasmon resonance (SPR) experiments, in vitro cell-based assays, and model high-fat diet (HFD)-induced obesity studies, heated FGF21 maintained biological activities that were comparable to those of non-heated and commercial FGF21s. Based on sequence comparison and structural analysis, five point-mutations were introduced into FGF21. Compared with the wild type, the heated FGF21 variant displayed improved therapeutic potential in terms of body weight loss, the levels of hepatic triglycerides and lipids, and the degree of vacuolization of liver in HFD-fed mice.

Domain-Specific Phase Transitions in a Supramolecular Nanostructure

Understanding thermal phase behavior within nanomaterials can inform their rational design for medical technologies like drug delivery systems and vaccines, as well as for energy technologies and catalysis. This study resolves thermal phases of discrete domains within a supramolecular aramid amphiphile (AA) nanoribbon. Dynamics are characterized by X-band EPR spectroscopy of spin labels positioned at specific sites through the nanoribbon cross-section. The fitting of the electron paramagnetic resonance (EPR) line shapes reveals distinct conformational dynamics, with fastest dynamics at the surface water layer, intermediate dynamics within the flexible cationic head group domain, and slowest dynamics in the interior aramid domain. Measurement of conformational mobility as a function of temperature reveals first- and second-order phase transitions, with melting transitions observed in the surface and head group domains and a temperature-insensitive crystalline phase in the aramid domain. Arrhenius analysis yields activation energies of diffusion at each site. This work demonstrates that distinct thermal phase behaviors between adjacent nanodomains within a supramolecular nanostructure may be resolved and illustrates the utility of EPR spectroscopy for thermal phase characterization of nanostructures.

Mammalian derived lipocalin and secretoglobin respiratory allergens strongly bind ligands with potentially immune modulating properties

Allergens from furry animals frequently cause sensitization and respiratory allergic diseases. Most relevant mammalian respiratory allergens belong either to the protein family of lipocalins or secretoglobins. Their mechanism of sensitization remains largely unresolved. Mammalian lipocalin and secretoglobin allergens are associated with a function in chemical communication that involves abundant secretion into the environment, high stability and the ability to transport small volatile compounds. These properties are likely to contribute concomitantly to their allergenic potential. In this study, we aim to further elucidate the physiological function of lipocalin and secretoglobin allergens and link it to their sensitizing capacity, by analyzing their ligand-binding characteristics. We produced eight major mammalian respiratory allergens from four pet species in E.coli and compared their ligand-binding affinities to forty-nine ligands of different chemical classes by using a fluorescence-quenching assay. Furthermore, we solved the crystal-structure of the major guinea pig allergen Cav p 1, a typical lipocalin. Recombinant lipocalin and secretoglobin allergens are of high thermal stability with melting temperatures ranging from 65 to 90°C and strongly bind ligands with dissociation constants in the low micromolar range, particularly fatty acids, fatty alcohols and the terpene alcohol farnesol, that are associated with potential semiochemical and/or immune-modulating functions. Through the systematic screening of respiratory mammalian lipocalin and secretoglobin allergens with a large panel of potential ligands, we observed that total amino acid composition, as well as cavity shape and volume direct affinities to ligands of different chemical classes. Therefore, we were able to categorize lipocalin allergens over their ligand-binding profile into three sub-groups of a lipocalin clade that is associated with functions in chemical communication, thus strengthening the function of major mammalian respiratory allergens as semiochemical carriers. The promiscuous binding capability of hydrophobic ligands from environmental sources warrants further investigation regarding their impact on a molecule's allergenicity.

Fluorescent cyclophanes and their applications

With the serendipitous discovery of crown ethers by Pedersen more than half a century ago and the subsequent introduction of host-guest chemistry and supramolecular chemistry by Cram and Lehn, respectively, followed by the design and synthesis of wholly synthetic cyclophanes-in particular, fluorescent cyclophanes, having rich structural characteristics and functions-have been the focus of considerable research activity during the past few decades. Cyclophanes with remarkable emissive properties have been investigated continuously over the years and employed in numerous applications across the field of science and technology. In this Review, we feature the recent developments in the chemistry of fluorescent cyclophanes, along with their design and synthesis. Their host-guest chemistry and applications related to their structure and properties are highlighted.

In silico analyses of acetylcholinesterase (AChE) and its genetic variants in interaction with the anti-Alzheimer drug Rivastigmine

Alzheimer's disease (AD) is the leading cause of dementia worldwide. Despite causing great social and economic impact, there is currently no cure for AD. The most effective therapy to manage AD symptoms is based on acetylcholinesterase inhibitors (AChEi), from which rivastigmine presented numerous benefits. However, mutations in AChE, which affect approximately 5% of the population, can modify protein structure and function, changing the individual response to Alzheimer's treatment. In this study, we performed computer simulations of AChE wild type and variants R34Q, P135A, V333E, and H353N, identified by one or more genome-wide association studies, to evaluate their effects on protein structure and interaction with rivastigmine. The functional effects of AChE variants were predicted using eight machine learning algorithms, while the evolutionary conservation of AChE residues was analyzed using the ConSurf server. Autodock4.2.6 was used to predict the binding modes for the hAChE-rivastigmine complex, which is still unknown. Molecular dynamics (MD) simulations were performed in triplicates for the AChE wild type and mutants using the GROMACS packages. Among the analyzed variants, P135A was classified as deleterious by all the functional prediction algorithms, in addition to occurring at highly conserved positions, which may have harmful consequences on protein function. The molecular docking results suggested that rivastigmine interacts with hAChE at the upper active-site gorge, which was further confirmed by MD simulations. Our MD findings also suggested that the complex hAChE-rivastigmine remains stable over time. The essential dynamics revealed flexibility alterations at the active-site gorge upon mutations P135A, V333E, and H353N, which may lead to strong and nonintuitive consequences to hAChE binding. Nonetheless, similar binding affinities were registered in the MMPBSA analysis for the hAChE wild type and variants when complexed to rivastigmine. Finally, our findings indicated that the rivastigmine binding to hAChE is an energetically favorable process mainly driven by negatively charged amino acids.

In silico investigation of riboswitches in fungi: structural and dynamical insights into TPP riboswitches in Aspergillus oryzae

Riboswitches are RNA sensors affecting post-transcriptional processes through their ability to bind to small molecules. Thiamine pyrophosphate (TPP) riboswitch plays a crucial role in regulating genes involved in synthesizing or transporting thiamine and phosphorylated derivatives in bacteria, archaea, plants, and fungi. Although TPP riboswitch is reasonably well known in bacteria, there is a gap in the knowledge of the fungal TPP riboswitches structure and dynamics, involving mainly sequence variation and TPP interaction with the aptamers. On the other hand, the increase of fungal infections and antifungal resistance raises the need for new antifungal therapies. In this work, we used computational approaches to build three-dimensional models for the three TPP riboswitches identified in Aspergillus oryzae, in which we studied their structure, dynamics, and binding free energy change (ΔG_bind) with TPP. Interaction patterns between the TPP and the surrounding nucleotides were conserved among the three models, evidencing high structural conservation. Furthermore, we show that the TPP riboswitch from the A. oryzae NMT1 gene behaves similarly to the E. coli thiA gene concerning the ΔG_bind. In contrast, mutations in the fungal TPP riboswitches from THI4 and the nucleoside transporter genes led to structural differences, affecting the binding-site volume, hydrogen bond occupancy, and ΔG_bind. Besides, the number of water molecules surrounding TPP influenced the ΔG_bind considerably. Notably, our ΔG_bind estimation agreed with previous experimental data, reinforcing the relationship between sequence conservation and TPP interaction.

Molecular dynamics and protein frustration analysis of human fused in Sarcoma protein variants in Amyotrophic Lateral Sclerosis type 6: An In Silico approach

Amyotrophic lateral sclerosis (ALS) is the most frequent adult-onset motor neuron disorder. The disease is characterized by degeneration of upper and lower motor neurons, leading to death usually within five years after the onset of symptoms. While most cases are sporadic, 5%-10% of cases can be associated with familial inheritance, including ALS type 6, which is associated with mutations in the Fused in Sarcoma (FUS) gene. This work aimed to evaluate how the most frequent ALS-related mutations in FUS, R521C, R521H, and P525L affect the protein structure and function. We used prediction algorithms to analyze the effects of the non-synonymous single nucleotide polymorphisms and performed evolutionary conservation analysis, protein frustration analysis, and molecular dynamics simulations. Most of the prediction algorithms classified the three mutations as deleterious. All three mutations were predicted to reduce protein stability, especially the mutation R521C, which was also predicted to increase chaperone binding tendency. The protein frustration analysis showed an increase in frustration in the interactions involving the mutated residue 521C. Evolutionary conservation analysis showed that residues 521 and 525 of human FUS are highly conserved sites. The molecular dynamics results indicate that protein stability could be compromised in all three mutations. They also affected the exposed surface area and protein compactness. The analyzed mutations also displayed high flexibility in most residues in all variants, most notably in the interaction site with the nuclear import protein of FUS.

Decline of protein structure rigidity with interatomic distance

BACKGROUND

Protein structural rigidity was analyzed in a non-redundant ensemble of high-resolution protein crystal structures by means of the Hirshfeld test, according to which the components (uX and uY) of the B-factors of two atoms (X and Y) along the interatomic direction is related to their degree of rigidity: the atoms may move as a rigid body if uX = uY and they cannot if uX ≠ uY.

RESULTS

It was observed that the rigidity degree diminishes if the number of covalent bonds intercalated between the two atoms (d_seq) increases, while it is rather independent on the Euclidean distance between the two atoms (d): for a given value of d_seq, the difference between uX and uY does not depend on d. No additional rigidity decline is observed when d_seq ≥  ~ 30 and this upper limit is very modest, close to 0.015 Å.

CONCLUSIONS

This suggests that protein flexibility is not fully described by B-factors that capture only partially the wide range of distortions that proteins can afford.

Conformational Adaptation of β-Peptide Foldamers for the Formation of Metal-Peptide Frameworks

Metal-coordinated frameworks derived from small peptidic ligands have received much attention thanks to peptides' vast structural and functional diversity. Various peptides with partial conformational preferences have been used to build metal-peptide frameworks, however, the use of conformationally constrained β-peptide foldamers has not been explored yet. Herein we report the first metal-coordination-mediated assembly of β-peptide foldamers with 12-helical folding propensity. The coordination of Ag⁺ to the terminal pyridyl moieties afforded a set of metal-peptide frameworks with unique entangled topologies. Interestingly, formation of the network structures was accompanied by notable conformational distortions of the foldamer ligands. As the first demonstration of new metal-peptide frameworks built from modular β-peptide foldamers, we anticipate that this work will be an important benchmark for further structural evolution and mechanistic investigation.

Comprehensive in silico analysis and molecular dynamics of the superoxide dismutase 1 (SOD1) variants related to amyotrophic lateral sclerosis

Amyotrophic Lateral Sclerosis (ALS) is the most frequent motor neuron disorder, with a significant social and economic burden. ALS remains incurable, and the only drugs approved for its treatments confers a survival benefit of a few months for the patients. Missense mutations in superoxide dismutase 1 (SOD1), a major cytoplasmic antioxidant enzyme, has been associated with ALS development, accounting for 23% of its familial cases and 7% of all sporadic cases. This work aims to characterize in silico the structural and functional effects of SOD1 protein variants. Missense mutations in SOD1 were compiled from the literature and databases. Twelve algorithms were used to predict the functional and stability effects of these mutations. ConSurf was used to estimate the evolutionary conservation of SOD1 amino-acids. GROMACS was used to perform molecular dynamics (MD) simulations of SOD1 wild-type and variants A4V, D90A, H46R, and I113T, which account for approximately half of all ALS-SOD1 cases in the United States, Europe, Japan, and United Kingdom, respectively. 233 missense mutations in SOD1 protein were compiled from the databases and literature consulted. The predictive analyses pointed to an elevated rate of deleterious and destabilizing predictions for the analyzed variants, indicating their harmful effects. The ConSurf analysis suggested that mutations in SOD1 mainly affect conserved and possibly functionally essential amino acids. The MD analyses pointed to flexibility and essential dynamics alterations at the electrostatic and metal-binding loops of variants A4V, D90A, H46R, and I113T that could lead to aberrant interactions triggering toxic protein aggregation. These alterations may have harmful implications for SOD1 and explain their association with ALS. Understanding the effects of SOD1 mutations on protein structure and function facilitates the design of further experiments and provides relevant information on the molecular mechanism of pathology, which may contribute to improvements in existing treatments for ALS.

Molecular dynamics analysis of the binding of human interleukin-6 with interleukin-6 α-receptor

Human interleukin-6 (hIL-6) is a multifunctional cytokine that regulates immune and inflammatory responses in addition to metabolic and regenerative processes and cancer. hIL-6 binding to the IL-6 receptor (IL-6Rα) induces homodimerization and recruitment of the glycoprotein (gp130) to form a hexameric signaling complex. Anti-IL-6 and IL-6R antibodies are clinically approved inhibitors of IL-6 signaling pathway for treating rheumatoid arthritis and Castleman's disease, respectively. There is a potential to develop novel small molecule IL-6 antagonists derived from understanding the structural basis for IL-6/IL-6Rα interactions. Here, we combine homology modeling with extensive molecular dynamics (MD) simulations to examine the association of hIL-6 with IL-6Rα. A comparison with MD of apo hIL-6 reveals that the binding of hIL-6 to IL-6Rα induces structural and dynamic rearrangements in the AB loop region of hIL-6, disrupting intraprotein contacts and increasing the flexibility of residues 48 to 58 of the AB loop. In contrast, due to the involvement of residues 59 to 78 in forming contacts with the receptor, these residues of the AB loop are observed to rigidify in the presence of the receptor. The binary complex is primarily stabilized by two pairs of salt bridges, Arg181 (hIL-6)- Glu182 (IL-6Rα) and Arg184 (hIL-6)- Glu183 (IL-6Rα) as well as hydrophobic and aromatic stacking interactions mediated essentially by Phe residues in both proteins. An interplay of electrostatic, hydrophobic, hydrogen bonding, and aromatic stacking interactions facilitates the formation of the hIL-6/IL-6Rα complex.

Molecular Model Construction of the Dense Medium Component Scaffold in Coal for Molecular Aggregate Simulation

Coal as an important fossil energy has been comprehensively studied in terms of its structure, reactivity, and application. However, there are few publications reported about the formation mechanism of coal. In order to explore the molecular mechanism of the formation of the dense medium component (DMC) aggregate, which is extracted from coal, the molecular model of the DMC scaffold (DMC-S) was constructed based on a number of X-ray photoelectron spectroscopy, ¹³C NMR, and ultimate analysis. Then, DMC-S was further optimized, and the periodic boundary condition was added for molecular mechanics and molecular dynamics simulation. The DMC-S molecule model with a density of 1.05 g/cm³ and a different number of unit cells was obtained after the aforementioned experiments and simulations. When the unit cell contained 12 DMC-S molecules, the absolute value of electrostatic energy significantly increased and the peripheral branch chains in DMC-S interlaced with each other, forming a compact aggregate. The density and macrosize calculated values are all slightly lower than the true relative values because the presence of minerals or small molecules was not included in the model construction. Despite some unavoidable defects, the comparison between the simulated and experimental results validates the DMC-S aggregate model and lays a solid foundation for an in-depth study of DMC and its reactivity.

In silico analysis of the tryptophan hydroxylase 2 (TPH2) protein variants related to psychiatric disorders

The tryptophan hydroxylase 2 (TPH2) enzyme catalyzes the first step of serotonin biosynthesis. Serotonin is known for its role in several homeostatic systems related to sleep, mood, and food intake. As the reaction catalyzed by TPH2 is the rate-limiting step of serotonin biosynthesis, mutations in TPH2 have been associated with several psychiatric disorders (PD). This work undertakes an in silico analysis of the effects of genetic mutations in the human TPH2 protein. Ten algorithms were used to predict the functional and stability effects of the TPH2 mutations. ConSurf was used to estimate the evolutionary conservation of TPH2 amino acids. GROMACS was used to perform molecular dynamics (MD) simulations of TPH2 WT and P260S, R303W, and R441H, which had already been associated with the development of PD. Forty-six TPH2 variants were compiled from the literature. Among the analyzed variants, those occurring at the catalytic domain were shown to be more damaging to protein structure and function. The ConSurf analysis indicated that the mutations affecting the catalytic domain were also more conserved throughout evolution. The variants S364K and S383F were predicted to be deleterious by all the functional algorithms used and occurred at conserved positions, suggesting that they might be deleterious. The MD analyses indicate that the mutations P206S, R303W, and R441H affect TPH2 flexibility and essential mobility at the catalytic and oligomerization domains. The variants P206S, R303W, and R441H also exhibited alterations in dimer binding affinity and stability throughout the simulations. Thus, these mutations may impair TPH2 functional interactions and, consequently, its function, leading to the development of PD. Furthermore, we developed a database, SNPMOL (http://www.snpmol.org/), containing the results presented in this paper. Understanding the effects of TPH2 mutations on protein structure and function may lead to improvements in existing treatments for PD and facilitate the design of further experiments.

Integrating Stimuli-Responsive Properties in Host-Guest Supramolecular Drug Delivery Systems

Host-guest motifs are likely the most recognizable manifestation of supramolecular chemistry. These complexes are characterized by the organization of small molecules on the basis of preferential association of a guest within the portal of a host. In the context of their therapeutic use, the primary application of these complexes has been as excipients which enhance the solubility or improve the stability of drug formulations, primarily in a vial. However, there may be opportunities to go significantly beyond such a role and leverage key features of the affinity, specificity, and dynamics of the interaction itself toward "smarter" therapeutic designs. One approach in this regard would seek stimuli-responsive host-guest recognition, wherein a complex forms in a manner that is sensitive to, or can be governed by, externally applied triggers, disease-specific proteins and analytes, or the presence of a competing guest. This review will highlight the general and phenomenological design considerations governing host-guest recognition and the specific types of chemistry which have been used and are available for different applications. Finally, a discussion of the molecular engineering and design approaches which enable sensitivity to a variety of different stimuli are highlighted. Ultimately, these molecular-scale approaches offer an assortment of new chemistry and material design tools toward improving precision in drug delivery.

The role of a weakly coordinating thioether group in ligation controlled molecular self-assemblies and their inter-conversions in Ni(ii) complexes of l-methionine derived ligand

A series of Ni(ii) complexes of an amino acid derived ligand (Salmet) has been synthesized, and characterized by various techniques including X-ray crystallography. Alkali ions K⁺/Na⁺ direct the conversion of monomers to multi-nuclear complexes.

A proline deletion in IFNAR1 impairs IFN-signaling and underlies increased resistance to tuberculosis in humans

Type I interferons (IFN), best known for their anti-viral functions, have been shown to impair host resistance to intracellular bacteria in mice. However, the precise role of type I IFN signaling in bacterial infection in humans is unclear. Here, we show that genetic variation in the human IFNAR1 gene is associated with decreased susceptibility to tuberculosis and an increased risk of viral hepatitis in Chinese populations. Receptor mutagenesis and cell signaling studies establish that the IFNAR1 mutation corresponding to a proline deletion in the hinge region of the membrane-proximal domain of IFNAR1 decreases the binding affinity of IFNAR1 to IFN-β, impeding type I IFN signaling. Our findings suggest that IFNAR1 signaling underlies an increased risk of tuberculosis in humans and reveals a function for the IFNAR1 inter-domain region in cytokine–cytokine receptor interaction and signal transduction.

The role of type I interferons in bacterial infection is less clear than it is in viral infection. Here, the authors show that genetic variation of the human IFNAR1 gene is associated with decreased susceptibility to tuberculosis and identify a role for the IFNAR1 inter-domain region in the cytokine response.

Relative Binding Free Energy Calculations in Drug Discovery: Recent Advances and Practical Considerations

Accurate in silico prediction of protein-ligand binding affinities has been a primary objective of structure-based drug design for decades due to the putative value it would bring to the drug discovery process. However, computational methods have historically failed to deliver value in real-world drug discovery applications due to a variety of scientific, technical, and practical challenges. Recently, a family of approaches commonly referred to as relative binding free energy (RBFE) calculations, which rely on physics-based molecular simulations and statistical mechanics, have shown promise in reliably generating accurate predictions in the context of drug discovery projects. This advance arises from accumulating developments in the underlying scientific methods (decades of research on force fields and sampling algorithms) coupled with vast increases in computational resources (graphics processing units and cloud infrastructures). Mounting evidence from retrospective validation studies, blind challenge predictions, and prospective applications suggests that RBFE simulations can now predict the affinity differences for congeneric ligands with sufficient accuracy and throughput to deliver considerable value in hit-to-lead and lead optimization efforts. Here, we present an overview of current RBFE implementations, highlighting recent advances and remaining challenges, along with examples that emphasize practical considerations for obtaining reliable RBFE results. We focus specifically on relative binding free energies because the calculations are less computationally intensive than absolute binding free energy (ABFE) calculations and map directly onto the hit-to-lead and lead optimization processes, where the prediction of relative binding energies between a reference molecule and new ideas (virtual molecules) can be used to prioritize molecules for synthesis. We describe the critical aspects of running RBFE calculations, from both theoretical and applied perspectives, using a combination of retrospective literature examples and prospective studies from drug discovery projects. This work is intended to provide a contemporary overview of the scientific, technical, and practical issues associated with running relative binding free energy simulations, with a focus on real-world drug discovery applications. We offer guidelines for improving the accuracy of RBFE simulations, especially for challenging cases, and emphasize unresolved issues that could be improved by further research in the field.

Molecular rigidity and enthalpy-entropy compensation in DNA melting

Enthalpy-entropy compensation (EEC) is observed in diverse molecular binding processes of importance to living systems and manufacturing applications, but this widely occurring phenomenon is not sufficiently understood from a molecular physics standpoint. To gain insight into this fundamental problem, we focus on the melting of double-stranded DNA (dsDNA) since measurements exhibiting EEC are extensive for nucleic acid complexes and existing coarse-grained models of DNA allow us to explore the influence of changes in molecular parameters on the energetic parameters by using molecular dynamics simulations. Previous experimental and computational studies have indicated a correlation between EEC and changes in molecular rigidity in certain binding-unbinding processes, and, correspondingly, we estimate measures of DNA molecular rigidity under a wide range of conditions, along with resultant changes in the enthalpy and entropy of binding. In particular, we consider variations in dsDNA rigidity that arise from changes of intrinsic molecular rigidity such as varying the associative interaction strength between the DNA bases, the length of the DNA chains, and the bending stiffness of the individual DNA chains. We also consider extrinsic changes of molecular rigidity arising from the addition of polymer additives and geometrical confinement of DNA between parallel plates. All our computations confirm EEC and indicate that this phenomenon is indeed highly correlated with changes in molecular rigidity. However, two distinct patterns relating to how DNA rigidity influences the entropy of association emerge from our analysis. Increasing the intrinsic DNA rigidity increases the entropy of binding, but increases in molecular rigidity from external constraints decreases the entropy of binding. EEC arises in numerous synthetic and biological binding processes and we suggest that changes in molecular rigidity might provide a common origin of this ubiquitous phenomenon in the mutual binding and unbinding of complex molecules.

A Demonstration of Le Chatelier's Principle on the Nanoscale

Photothermal desorption of molecules from plasmonic nanoparticles is an example of a light-triggered molecular release due to heating of the system. However, this phenomenon ought to work only if the molecule-nanoparticle interaction is exothermic in nature. In this study, we compare protein adsorption behavior onto gold nanoparticles for both endothermic and exothermic complexation reactions, and demonstrate that Le Chatelier's principle can be applied to predict protein adsorption or desorption on nanomaterial surfaces. Polyelectrolyte-wrapped gold nanorods were used as adsorption platforms for two different proteins, which we were able to adsorb/desorb from the nanorod surface depending on the thermodynamics of their interactions. Furthermore, we show that the behaviors hold up under more complex biological environments such as fetal bovine serum.

Increased Conformational Flexibility of a Macrocycle-Receptor Complex Contributes to Reduced Dissociation Rates

Constraining a peptide in its bioactive conformation by macrocyclization represents a powerful strategy to design modulators of challenging biomolecular targets. This holds particularly true for the development of inhibitors of protein‐protein interactions which often involve interfaces lacking defined binding pockets. Such flat surfaces are demanding targets for traditional small molecules rendering macrocyclic peptides promising scaffolds for novel therapeutics. However, the contribution of peptide dynamics to binding kinetics is barely understood which impedes the design process. Herein, we report unexpected trends in the binding kinetics of two closely related macrocyclic peptides that bind their receptor protein with high affinity. Isothermal titration calorimetry, ¹⁹F NMR experiments and molecular dynamics simulations reveal that increased conformational flexibility of the macrocycle–receptor complex reduces dissociation rates and contributes to complex stability. This observation has impact on macrocycle design strategies that have so far mainly focused on the stabilization of bioactive ligand conformations.

Exploring the impact of the side-chain length on peptide/RNA binding events

The impact of the amino-acid side-chain length on peptide-RNA binding events has been investigated using HIV-1 Tat derived peptides as ligands and the HIV-1 TAR RNA element as an RNA model. Our studies demonstrate that increasing the length of all peptide side-chains improves unexpectedly the binding affinity (K_D) but reduces the degree of compactness of the peptide-RNA complex. Overall, the side-chain length appears to modulate in an unpredictable way the ability of the peptide to compete with the cognate TAR RNA partner. Beyond the establishment of non-intuitive fundamental relationships, our results open up new perspectives in the design of effective RNA ligand competitors, since a large number of them have already been identified but few studies report on the modulation of the biological activity by modifying in the same way the length of all chains connecting RNA recognition motives to the central scaffold of a ligand.

The Dynameomics Entropy Dictionary: A Large-Scale Assessment of Conformational Entropy across Protein Fold Space

Molecular dynamics (MD) simulations contain considerable information with regard to the motions and fluctuations of a protein, the magnitude of which can be used to estimate conformational entropy. Here we survey conformational entropy across protein fold space using the Dynameomics database, which represents the largest existing data set of protein MD simulations for representatives of essentially all known protein folds. We provide an overview of MD-derived entropies accounting for all possible degrees of dihedral freedom on an unprecedented scale. Although different side chains might be expected to impose varying restrictions on the conformational space that the backbone can sample, we found that the backbone entropy and side chain size are not strictly coupled. An outcome of these analyses is the Dynameomics Entropy Dictionary, the contents of which have been compared with entropies derived by other theoretical approaches and experiment. As might be expected, the conformational entropies scale linearly with the number of residues, demonstrating that conformational entropy is an extensive property of proteins. The calculated conformational entropies of folding agree well with previous estimates. Detailed analysis of specific cases identifies deviations in conformational entropy from the average values that highlight how conformational entropy varies with sequence, secondary structure, and tertiary fold. Notably, α-helices have lower entropy on average than do β-sheets, and both are lower than coil regions.

Polypharmacology: in silico methods of ligand design and development

How to design a ligand to bind multiple targets, rather than to a single target, is the focus of this review. Rational polypharmacology draws on knowledge that is both broad ranging and hierarchical. Computer-aided multitarget ligand design methods are described according to their nested knowledge level. Ligand-only and then receptor-ligand strategies are first described; followed by the metabolic network viewpoint. Subsequently strategies that view infectious diseases as multigenomic targets are discussed, and finally the disease level interpretation of medicinal therapy is considered. As yet there is no consensus on how best to proceed in designing a multitarget ligand. The current methodologies are bought together in an attempt to give a practical overview of how polypharmacology design might be best initiated.

Quasithermodynamic contributions to the fluctuations of a protein nanopore

Proteins undergo thermally activated conformational fluctuations among two or more substates, but a quantitative inquiry on their kinetics is persistently challenged by numerous factors, including the complexity and dynamics of various interactions, along with the inability to detect functional substates within a resolvable time scale. Here, we analyzed in detail the current fluctuations of a monomeric β-barrel protein nanopore of known high-resolution X-ray crystal structure. We demonstrated that targeted perturbations of the protein nanopore system, in the form of loop-deletion mutagenesis, accompanying alterations of electrostatic interactions between long extracellular loops, produced modest changes of the differential activation free energies calculated at 25 °C, ΔΔG(⧧), in the range near the thermal energy but substantial and correlated modifications of the differential activation enthalpies, ΔΔH(⧧), and entropies, ΔΔS(⧧). This finding indicates that the local conformational reorganizations of the packing and flexibility of the fluctuating loops lining the central constriction of this protein nanopore were supplemented by changes in the single-channel kinetics. These changes were reflected in the enthalpy-entropy reconversions of the interactions between the loop partners with a compensating temperature, TC, of ∼300 K, and an activation free energy constant of ∼41 kJ/mol. We also determined that temperature has a much greater effect on the energetics of the equilibrium gating fluctuations of a protein nanopore than other environmental parameters, such as the ionic strength of the aqueous phase as well as the applied transmembrane potential, likely due to ample changes in the solvation activation enthalpies. There is no fundamental limitation for applying this approach to other complex, multistate membrane protein systems. Therefore, this methodology has major implications in the area of membrane protein design and dynamics, primarily by revealing a better quantitative assessment on the equilibrium transitions among multiple well-defined and functionally distinct substates of protein channels and pores.

Efficient in silico exploration of RNA interhelical conformations using Euler angles and WExplore

HIV-1 TAR RNA is a two-helix bulge motif that plays a critical role in HIV viral replication and is an important drug target. However, efforts at designing TAR inhibitors have been challenged by its high degree of structural flexibility, which includes slow large-amplitude reorientations of its helices with respect to one another. Here, we use the recently introduced algorithm WExplore in combination with Euler angles to achieve unprecedented sampling of the TAR conformational ensemble. Our ensemble achieves similar agreement with experimental NMR data when compared with previous TAR computational studies, and is generated at a fraction of the computational cost. It clearly emerges from configuration space network analysis that the intermittent formation of the A22-U40 base pair acts as a reversible switch that enables sampling of interhelical conformations that would otherwise be topologically disallowed. We find that most previously determined ligand-bound structures are found in similar location in the network, and we use a sample-and-select approach to guide the construction of a set of novel conformations which can serve as the basis for future drug development efforts. Collectively, our findings demonstrate the utility of WExplore in combination with suitable order parameters as a method for exploring RNA conformational space.

Organelle-mimicking liposome dissociates G-quadruplexes and facilitates transcription

Important biological reactions involving nucleic acids occur near the surface of membranes such as the nuclear membrane (NM) and rough endoplasmic reticulum (ER); however, the interactions between biomembranes and nucleic acids are poorly understood. We report here that transcription was facilitated in solution with liposomes, which mimic a biomembrane surface, relative to the reaction in a homogeneous aqueous solution when the template was able to form a G-quadruplex. The G-quadruplex is known to be an inhibitor of transcription, but the stability of the G-quadruplex was decreased at the liposome surface because of unfavourable enthalpy. The destabilization of the G-quadruplex was greater at the surface of NM- and ER-mimicking liposomes than at the surfaces of liposomes designed to mimic other organelles. Thermodynamic analyses revealed that the G-rich oligonucleotides adopted an extended structure at the liposome surface, whereas in solution the compact G-quadruplex was formed. Our data suggest that changes in structure and stability of nucleic acids regulate biological reactions at membrane surfaces.

Prediction and validation of diffusion coefficients in a model drug delivery system using microsecond atomistic molecular dynamics simulation and vapour sorption analysis

Diffusion of small to medium sized molecules in polymeric medical device materials underlies a broad range of public health concerns related to unintended leaching from or uptake into implantable medical devices. However, obtaining accurate diffusion coefficients for such systems at physiological temperature represents a formidable challenge, both experimentally and computationally. While molecular dynamics simulation has been used to accurately predict the diffusion coefficients, D, of a handful of gases in various polymers, this success has not been extended to molecules larger than gases, e.g., condensable vapours, liquids, and drugs. We present atomistic molecular dynamics simulation predictions of diffusion in a model drug eluting system that represent a dramatic improvement in accuracy compared to previous simulation predictions for comparable systems. We find that, for simulations of insufficient duration, sub-diffusive dynamics can lead to dramatic over-prediction of D. We present useful metrics for monitoring the extent of sub-diffusive dynamics and explore how these metrics correlate to error in D. We also identify a relationship between diffusion and fast dynamics in our system, which may serve as a means to more rapidly predict diffusion in slowly diffusing systems. Our work provides important precedent and essential insights for utilizing atomistic molecular dynamics simulations to predict diffusion coefficients of small to medium sized molecules in condensed soft matter systems.

A fundamental view of enthalpy–entropy compensation

There is no fundamental difference in enthalpy–entropy compensation between dispersion and electrostatics or between quantum and molecular mechanics.

Receptor-ligand molecular docking

Docking methodology aims to predict the experimental binding modes and affinities of small molecules within the binding site of particular receptor targets and is currently used as a standard computational tool in drug design for lead compound optimisation and in virtual screening studies to find novel biologically active molecules. The basic tools of a docking methodology include a search algorithm and an energy scoring function for generating and evaluating ligand poses. In this review, we present the search algorithms and scoring functions most commonly used in current molecular docking methods that focus on protein-ligand applications. We summarise the main topics and recent computational and methodological advances in protein-ligand docking. Protein flexibility, multiple ligand binding modes and the free-energy landscape profile for binding affinity prediction are important and interconnected challenges to be overcome by further methodological developments in the docking field.

Thermodynamic studies of a series of homologous HIV-1 TAR RNA ligands reveal that loose binders are stronger Tat competitors than tight ones

RNA is a major drug target, but the design of small molecules that modulate RNA function remains a great challenge. In this context, a series of structurally homologous 'polyamide amino acids' (PAA) was studied as HIV-1 trans-activating response (TAR) RNA ligands. An extensive thermodynamic study revealed the occurence of an enthalpy-entropy compensation phenomenon resulting in very close TAR affinities for all PAA. However, their binding modes and their ability to compete with the Tat fragment strongly differ according to their structure. Surprisingly, PAA that form loose complexes with TAR were shown to be stronger Tat competitors than those forming tight ones, and thermal denaturation studies demonstrated that loose complexes are more stable than tight ones. This could be correlated to the fact that loose and tight ligands induce distinct RNA conformational changes as revealed by circular dichroism experiments, although nuclear magnetic resonance (NMR) experiments showed that the TAR binding site is the same in all cases. Finally, some loose PAA also display promising inhibitory activities on HIV-infected cells. Altogether, these results lead to a better understanding of RNA interaction modes that could be very useful for devising new ligands of relevant RNA targets.

Entropy-enthalpy compensation: role and ramifications in biomolecular ligand recognition and design

Recent calorimetric studies of interactions between small molecules and biomolecular targets have generated renewed interest in the phenomenon of entropy-enthalpy compensation. In these studies, entropic and enthalpic contributions to binding are observed to vary substantially and in an opposing manner as the ligand or protein is modified, whereas the binding free energy varies little. In severe examples, engineered enthalpic gains can lead to completely compensating entropic penalties, frustrating ligand design. Here, we examine the evidence for compensation, as well as its potential origins, prevalence, severity, and ramifications for ligand engineering. We find the evidence for severe compensation to be weak in light of the large magnitude of and correlation between errors in experimental measurements of entropic and enthalpic contributions to binding, though a limited form of compensation may be common. Given the difficulty of predicting or measuring entropic and enthalpic changes to useful precision, or using this information in design, we recommend ligand engineering efforts instead focus on computational and experimental methodologies to directly assess changes in binding free energy.