Normal mode analysis of biomolecular structures: functional mechanisms of membrane proteins

Structural shifts in TolC facilitate Efflux-Mediated β-lactam resistance

Efflux-mediated β-lactam resistance is a major public health concern, reducing the effectiveness of β-lactam antibiotics against many bacteria. Structural analyses show the efflux protein TolC in Gram-negative bacteria acts as a channel for antibiotics, impacting bacterial susceptibility and virulence. This study examines β-lactam drug efflux mediated by TolC using experimental and computational methods. Molecular dynamics simulations of drug-free TolC reveal essential movements and key residues involved in TolC opening. A whole-gene-saturation mutagenesis assay, mutating each TolC residue and measuring fitness effects under β-lactam selection, is performed. Here we show the TolC-mediated efflux of three antibiotics: oxacillin, piperacillin, and carbenicillin. Steered molecular dynamics simulations identify general and drug-specific efflux mechanisms, revealing key positions at TolC's periplasmic entry affecting efflux motions. Our findings provide insights into TolC's structural dynamics, aiding the design of new antibiotics to overcome bacterial efflux mechanisms.

The C-terminal self-binding helical peptide of human estrogen-related receptor γ can be druggably targeted by a novel class of rationally designed peptidic antagonists

Orphan nuclear estrogen-related receptor γ (ERRγ) has been recognized as a potential therapeutic target for cancer, inflammation and metabolic disorder. The ERRγ contains a regulatory AF2 helical tail linked C-terminally to its ligand-binding domain (LBD), which is a self-binding peptide (SBP) and serves as molecular switch to dynamically regulate the receptor alternation between active and inactive states by binding to and unbinding from the AF2-binding site on ERRγ LBD surface, respectively. Traditional ERRγ modulators are all small-molecule chemical ligands that can be classified into agonists and inverse agonists in terms of their action mechanism; the agonists stabilize the AF2 in ABS site with an agonist conformation, while the inverse agonists lock the AF2 out of the site to largely abolish ERRγ transcriptional activity. Here, a class of ERRγ peptidic antagonists was described to compete with native AF2 for the ABS site, thus blocking the active state of AF2 binding to ERRγ LBD domain. Self-inhibitory peptide was derived from the SBP-covering AF2 region and we expected it can rebind potently to the ABS site by reducing its intrinsic disorder and entropy cost upon the rebinding. Hydrocarbon stapling was employed to do so, which employed an all-hydrocarbon bridge across the [i, i + 4]-anchor residue pair in the N-terminal, middle or C-terminal region of the self-inhibitory peptide. As might be expected, it is revealed that the stapled peptides are good binders of ERRγ LBD domain and can effectively compete with the native AF2 helical tail for ERRγ ABS site, which exhibit a basically similar binding mode with AF2 to the site and form diverse noncovalent interactions with the site, thus conferring stability and specificity to the domain-peptide complexes.

Nanomechanical collective vibration of SARS-CoV-2 spike proteins

The development of effective therapeutics against COVID-19 requires a thorough understanding of the receptor recognition mechanism of the SARS-CoV-2 spike (S) protein. Here the multidomain collective dynamics on the trimer of the spike protein has been analyzed using normal mode analysis (NMA). A common nanomechanical profile was identified in the spike proteins of SARS-CoV-2 and its variants. The profile involves collective vibrations of the receptor-binding domain (RBD) and the N-terminal domain (NTD), which may mediate the physical interaction process. Quantitative analysis of the collective modes suggests a nanomechanical property involving large-scale conformational changes, which explains the difference in receptor binding affinity among different variants. These results support the use of intrinsic global dynamics as a valuable perspective for studying the allosteric and functional mechanisms of the S protein. This approach also provides a low-cost theoretical toolkit for screening potential pathogenic mutations and drug targets.

Micro-second time-resolved X-ray single-molecule internal motions of SARS-CoV-2 spike variants

Single-molecule intramolecular dynamics were successfully measured for three variants of SARS-CoV-2 spike protein, alpha: B.1.1.7, delta: B.1.617, and omicron: B.1.1.529, with a time resolution of 100 μs using X-rays. The results were then compared with respect to the magnitude and directions of motions for the three variants. The largest 3-D intramolecular movement was observed for the omicron variant irrespective of ACE2 receptor binding. A more detailed analysis of the intramolecular motions revealed that the distribution state of intramolecular motion for the three variants was completely different with and without ACE2 receptor binding. The molecular dynamics for the trimeric spike protein of the omicron variant increased when ACE2 binding occurred. At that time, the diffusion constant increased from 71.0 [mrad2/ms] to 91.1 [mrad2/ms].

Anisotropic Network Analysis of Open/Closed HCN4 Channel Advocates Asymmetric Subunit Cooperativity in cAMP Modulation of Gating

Hyperpolarization-activated cyclic nucleotide-modulated (HCN) channels are opened in an allosteric manner by membrane hyperpolarization and cyclic nucleotides such as cAMP. Because of conflicting reports from experimental studies on whether cAMP binding to the four available binding sites in the channel tetramer operates cooperatively in gating, we employ here a computational approach as a promising route to examine ligand-induced conformational changes after binding to individual sites. By combining an elastic network model (ENM) with linear response theory (LRT) for modeling the apo-holo transition of the cyclic nucleotide-binding domain (CNBD) in HCN channels, we observe a distinct pattern of cooperativity matching the "positive-negative-positive" cooperativity reported from functional studies. This cooperativity pattern is highly conserved among HCN subtypes (HCN4, HCN1), but only to a lesser extent visible in structurally related channels, which are only gated by voltage (KAT1) or cyclic nucleotides (TAX4). This suggests an inherent cooperativity between subunits in HCN channels as part of a ligand-triggered gating mechanism in these channels.

Immunoinformatics and Reverse Vaccinology Approach for the Identification of Potential Vaccine Candidates against Vandammella animalimors

Vandammella animalimorsus is a Gram-negative and non-motile bacterium typically transmitted to humans through direct contact with the saliva of infected animals, primarily through biting, scratches, or licks on fractured skin. The absence of a confirmed post-exposure treatment of V. animalimorsus bacterium highlights the imperative for developing an effective vaccine. We intended to determine potential vaccine candidates and paradigm a chimeric vaccine against V. animalimorsus by accessible public data analysis of the strain by utilizing reverse vaccinology. By subtractive genomics, five outer membranes were prioritized as potential vaccine candidates out of 2590 proteins. Based on the instability index and transmembrane helices, a multidrug transporter protein with locus ID A0A2A2AHJ4 was designated as a potential candidate for vaccine construct. Sixteen immunodominant epitopes were retrieved by utilizing the Immune Epitope Database. The epitope encodes the strong binding affinity, nonallergenic properties, non-toxicity, high antigenicity scores, and high solubility revealing the more appropriate vaccine construct. By utilizing appropriate linkers and adjuvants alongside a suitable adjuvant molecule, the epitopes were integrated into a chimeric vaccine to enhance immunogenicity, successfully eliciting both adaptive and innate immune responses. Moreover, the promising physicochemical features, the binding confirmation of the vaccine to the major innate immune receptor TLR-4, and molecular dynamics simulations of the designed vaccine have revealed the promising potential of the selected candidate. The integration of computational methods and omics data has demonstrated significant advantages in discovering novel vaccine targets and mitigating vaccine failure rates during clinical trials in recent years.

Normal Mode Analysis Elicits Conformational Shifts in Proteins at Both Proximal and Distal Regions to the Phosphosite Stemming from Single-Site Phosphorylation

Phosphorylation, a fundamental biochemical switch, intricately regulates protein function and signaling pathways. Our study employs extensive computational structural analyses on a curated data set of phosphorylated and unphosphorylated protein pairs to explore the multifaceted impact of phosphorylation on protein conformation. Using normal mode analysis (NMA), we investigated changes in protein flexibility post-phosphorylation, highlighting an enhanced level of structural dynamism. Our findings reveal that phosphorylation induces not only local changes at the phosphorylation site but also extensive alterations in distant regions, showcasing its far-reaching influence on protein structure-dynamics. Through in-depth case studies on polyubiquitin B and glycogen synthase kinase-3 beta, we elucidate how phosphorylation at distinct sites leads to variable structural and dynamic modifications, potentially dictating functional outcomes. While phosphorylation largely preserves the residue motion correlation, it significantly disrupts low-frequency global modes, presenting a dualistic impact on protein dynamics. We also explored alterations in the total accessible surface area (ASA), emphasizing region-specific changes around phosphorylation sites. This study sheds light on phosphorylation-induced conformational changes, dynamic modulation, and surface accessibility alterations, leveraging an integrated computational approach with RMSD, NMA, and ASA, thereby contributing to a comprehensive understanding of cellular regulation and suggesting promising avenues for therapeutic interventions.

Scalable computation of anisotropic vibrations for large macromolecular assemblies

The Normal Mode Analysis (NMA) is a standard approach to elucidate the anisotropic vibrations of macromolecules at their folded states, where low-frequency collective motions can reveal rearrangements of domains and changes in the exposed surface of macromolecules. Recent advances in structural biology have enabled the resolution of megascale macromolecules with millions of atoms. However, the calculation of their vibrational modes remains elusive due to the prohibitive cost associated with constructing and diagonalizing the underlying eigenproblem and the current approaches to NMA are not readily adaptable for efficient parallel computing on graphic processing unit (GPU). Here, we present eigenproblem construction and diagonalization approach that implements level-structure bandwidth-reducing algorithms to transform the sparse computation in NMA to a globally-sparse-yet-locally-dense computation, allowing batched tensor products to be most efficiently executed on GPU. We map, optimize, and compare several low-complexity Krylov-subspace eigensolvers, supplemented by techniques such as Chebyshev filtering, sum decomposition, external explicit deflation and shift-and-inverse, to allow fast GPU-resident calculations. The method allows accurate calculation of the first 1000 vibrational modes of some largest structures in PDB ( > 2.4 million atoms) at least 250 times faster than existing methods.

A Fresh Look at the Normal Mode Analysis of Proteins: Introducing Allosteric Co-Vibrational Modes

We propose a new way of utilizing normal modes to study protein conformational transitions. Instead of considering individual modes independently, we show that a weighted mixture of low-frequency vibrational modes can reveal dynamic information about the conformational mechanism in more detail than any single mode can. The weights in the mixed mode, termed the allosteric covibrational mode, are determined using a simple model where the conformational transition is viewed as a perturbation of the coupled harmonic oscillator associated with either of the two conformations. We demonstrate our theory in a biologically relevant example of high pharmaceutical interest involving the V617F mutation of Janus 2 tyrosine kinase (JAK2).

Designing of a multi-epitopes based vaccine against Haemophilius parainfluenzae and its validation through integrated computational approaches

Haemophilus parainfluenzae is a Gram-negative opportunist pathogen within the mucus of the nose and mouth without significant symptoms and has an ability to cause various infections ranging from ear, eye, and sinus to pneumonia. A concerning development is the increasing resistance of H. parainfluenzae to beta-lactam antibiotics, with the potential to cause dental infections or abscesses. The principal objective of this investigation is to utilize bioinformatics and immuno-informatic methodologies in the development of a candidate multi-epitope Vaccine. The investigation focuses on identifying potential epitopes for both B cells (B lymphocytes) and T cells (helper T lymphocytes and cytotoxic T lymphocytes) based on high non-toxic and non-allergenic characteristics. The selection process involves identifying human leukocyte antigen alleles demonstrating strong associations with recognized antigenic and overlapping epitopes. Notably, the chosen alleles aim to provide coverage for 90% of the global population. Multi-epitope constructs were designed by using suitable linker sequences. To enhance the immunological potential, an adjuvant sequence was incorporated using the EAAAK linker. The final vaccine construct, comprising 344 amino acids, was achieved after the addition of adjuvants and linkers. This multi-epitope Vaccine demonstrates notable antigenicity and possesses favorable physiochemical characteristics. The three-dimensional conformation underwent modeling and refinement, validated through in-silico methods. Additionally, a protein-protein molecular docking analysis was conducted to predict effective binding poses between the multi-epitope Vaccine and the Toll-like receptor 4 protein. The Molecular Dynamics (MD) investigation of the docked TLR4-vaccine complex demonstrated consistent stability over the simulation period, primarily attributed to electrostatic energy. The docked complex displayed minimal deformation and enhanced rigidity in the motion of residues during the dynamic simulation. Furthermore, codon translational optimization and computational cloning was performed to ensure the reliability and proper expression of the multi-Epitope Vaccine. It is crucial to emphasize that despite these computational validations, experimental research in the laboratory is imperative to demonstrate the immunogenicity and protective efficacy of the developed vaccine. This would involve practical assessments to ascertain the real-world effectiveness of the multi-epitope Vaccine.

Surveying the energy landscape of coarse-grained mappings

Simulations of soft materials often adopt low-resolution coarse-grained (CG) models. However, the CG representation is not unique and its impact upon simulated properties is poorly understood. In this work, we investigate the space of CG representations for ubiquitin, which is a typical globular protein with 72 amino acids. We employ Monte Carlo methods to ergodically sample this space and to characterize its landscape. By adopting the Gaussian network model as an analytically tractable atomistic model for equilibrium fluctuations, we exactly assess the intrinsic quality of each CG representation without introducing any approximations in sampling configurations or in modeling interactions. We focus on two metrics, the spectral quality and the information content, that quantify the extent to which the CG representation preserves low-frequency, large-amplitude motions and configurational information, respectively. The spectral quality and information content are weakly correlated among high-resolution representations but become strongly anticorrelated among low-resolution representations. Representations with maximal spectral quality appear consistent with physical intuition, while low-resolution representations with maximal information content do not. Interestingly, quenching studies indicate that the energy landscape of mapping space is very smooth and highly connected. Moreover, our study suggests a critical resolution below which a "phase transition" qualitatively distinguishes good and bad representations.

Convergence and equilibrium in molecular dynamics simulations

Molecular dynamics is a powerful tool that has been long used for the simulation of biomolecules. It complements experiments, by providing detailed information about individual atomic motions. But there is an essential and often overlooked assumption that, left unchecked, could invalidate any results from it: is the simulated trajectory long enough, so that the system has reached thermodynamic equilibrium, and the measured properties are converged? Previous studies showed mixed results in relation to this assumption. This has profound implications, as the resulting simulated trajectories may not be reliable in predicting equilibrium properties. Yet, this is precisely what most molecular dynamics studies do. So the question arises: are these studies even valid?Here, we present a thorough analysis of up to a hundred microseconds long trajectories, of several system with varying size, to probe the convergence of different structural, dynamical and cumulative properties, and elaborate on the relevance of the concept of equilibrium, and its physical and biological meaning. The results show that properties with the most biological interest tend to converge in multi-microsecond trajectories, although other properties-like transition rates to low probability conformations-may require more time.

How alginate lyase produces quasi-monodisperse oligosaccharides: A normal-mode-based docking and molecular dynamics simulation study

Oligosaccharide degradation products of alginate (AOS) hold significant potential in diverse fields, including pharmaceuticals, health foods, textiles, and agricultural production. Enzymatic alginate degradation is appealing due to its mild conditions, predictable activity, high yields, and controllability. However, the alginate degradation often results in a complex mixture of oligosaccharides, necessitating costly purification to isolate highly active oligosaccharides with a specific degree of polymerization (DP). Addressing this, our study centers on the alginate lyase AlyB from Vibrio Splendidus OU02, which uniquely breaks down alginate into mono-distributed trisaccharides. This enzyme features a polysaccharide lyase family 7 domain (PL-7) and a CBM32 carbohydrate-binding module connected by a helical structure. Through normal-mode-based docking and all-atom molecular simulations, we demonstrate that AlyB's substrate and product specificities are influenced by the spatial conformation of the catalytic pocket and the flexibility of its structure. The helically attached CBM is pivotal in releasing trisaccharides, which is crucial for avoiding further degradation. This study sheds light on AlyB's specificity and efficiency and contributes to the evolving field of enzyme design for producing targeted oligosaccharides, with significant implications for various bioindustries.

Oliveira AS, Mulholland AJ, Serapian SA, Colombo G. Decrypting Allostery in Membrane-Bound K-Ras4B Using Complementary In Silico Approaches Based on Unbiased Molecular Dynamics Simulations

Protein functions are dynamically regulated by allostery, which enables conformational communication even between faraway residues, and expresses itself in many forms, akin to different "languages": allosteric control pathways predominating in an unperturbed protein are often unintuitively reshaped whenever biochemical perturbations arise (e.g., mutations). To accurately model allostery, unbiased molecular dynamics (MD) simulations require integration with a reliable method able to, e.g., detect incipient allosteric changes or likely perturbation pathways; this is because allostery can operate at longer time scales than those accessible by plain MD. Such methods are typically applied singularly, but we here argue their joint application─as a "multilingual" approach─could work significantly better. We successfully prove this through unbiased MD simulations (∼100 μs) of the widely studied, allosterically active oncotarget K-Ras4B, solvated and embedded in a phospholipid membrane, from which we decrypt allostery using four showcase "languages": Distance Fluctuation analysis and the Shortest Path Map capture allosteric hotspots at equilibrium; Anisotropic Thermal Diffusion and Dynamical Non-Equilibrium MD simulations assess perturbations upon, respectively, either superheating or hydrolyzing the GTP that oncogenically activates K-Ras4B. Chosen "languages" work synergistically, providing an articulate, mutually coherent, experimentally consistent picture of K-Ras4B allostery, whereby distinct traits emerge at equilibrium and upon GTP cleavage. At equilibrium, combined evidence confirms prominent allosteric communication from the membrane-embedded hypervariable region, through a hub comprising helix α5 and sheet β5, and up to the active site, encompassing allosteric "switches" I and II (marginally), and two proposed pockets. Upon GTP cleavage, allosteric perturbations mostly accumulate on the switches and documented interfaces.

Potential Antidiabetic Activity of β-sitosterol from Zingiber roseum Rosc. via Modulation of Peroxisome Proliferator-activated Receptor Gamma (PPARγ)

AIM

To evaluate the antidiabetic potential of β-sitosterol from Zingiber roseum.

BACKGROUND

Diabetes mellitus is a cluster of metabolic disorders, and 90% of diabetic patients are affected with Type II diabetes (DM2). For the treatment of DM2, thiazolidinedione drugs (TZDs) were proposed, but recent studies have shown that TZDs have several detrimental effects, such as weight gain, kidney enlargement (hypertrophy), fluid retention, increased risk of bone fractures, and potential harm to the liver (hepatotoxicity). That is why a new molecule is needed to treat DM2.

OBJECTIVE

The current research aimed to assess the efficacy of β-Sitosterol from methanolic extract of Zingiber roseum in managing diabetes via PPARγ modulation.

METHODS

Zingiber roseum was extracted using methanol, and GC-MS was employed to analyze the extract. Through homology modeling, PPARγ structure was predicted. Molecular docking, MD simulation, free binding energies, QSAR, ADMET, and bioactivity and toxicity scores were all used during the in-depth computer-based research.

RESULTS

Clinically, agonists of synthetic thiazolidinedione (TZDs) have been used therapeutically to treat DM2, but these TZDs are associated with significant risks. Hence, GC-MS identified phytochemicals to search for a new PPAR-γ agonist. Based on the in-silico investigation, β-sitosterol was found to have a higher binding affinity (-8.9 kcal/mol) than standard drugs. MD simulations and MMGBSA analysis also demonstrated that β-sitosterol bound to the PPAR-γ active site stably.

CONCLUSION

It can be concluded that β-sitosterol from Z. roseum attenuates Type-II diabetes by modulating PPARγ activity.

A Structure-Based Allosteric Modulator Design Paradigm

Importance: Allosteric drugs bound to topologically distal allosteric sites hold a substantial promise in modulating therapeutic targets deemed undruggable at their orthosteric sites. Traditionally, allosteric modulator discovery has predominantly relied on serendipitous high-throughput screening. Nevertheless, the landscape has undergone a transformative shift due to recent advancements in our understanding of allosteric modulation mechanisms, coupled with a significant increase in the accessibility of allosteric structural data. These factors have extensively promoted the development of various computational methodologies, especially for machine-learning approaches, to guide the rational design of structure-based allosteric modulators. Highlights: We here presented a comprehensive structure-based allosteric modulator design paradigm encompassing 3 critical stages: drug target acquisition, allosteric binding site, and modulator discovery. The recent advances in computational methods in each stage are encapsulated. Furthermore, we delve into analyzing the successes and obstacles encountered in the rational design of allosteric modulators. Conclusion: The structure-based allosteric modulator design paradigm holds immense potential for the rational design of allosteric modulators. We hope that this review would heighten awareness of the use of structure-based computational methodologies in advancing the field of allosteric drug discovery.

Investigation on the molecular, electronic and spectroscopic properties of rosmarinic acid: an intuition from an experimental and computational perspective

Various drugs such as corticosteroids, salbutamol, and β2 agonist are available for the treatment of asthma an inflammatory disease and its symptoms, although the ingredient and the mode of action of these drugs are not clearly elucidated. Hence this research aimed at carrying out improved scientific research with respect to the use of natural product rosmarinic acid which poses minima, side effects. Herein, we first carried out extraction, isolation, and spectroscopic (FT-IR, 1H-NMR and 13C-NMR) investigation, followed by molecular modeling analysis on the naturally occurring rosmarinic acid extracted from Rosmarinus officinalis. A detailed comparison of the experimental and theoretical vibrational analysis has been carried out using five DFT functionals: BHANDH, HSEH1PBE, M06-2X, MPW3PBE and THCTHHYB with the basis set 6-311++G (d, p) to investigate into the structural, reactivity, and stability of the isolated compound. Frontier molecular orbital analysis and appropriate quantum descriptors were calculated. Results showed that the compound was more stable at M06-2X and more reactive at HSEH1PBE with an energy gap of 6.43441 eV and 3.8047 eV, respectively, which was later affirmed by the global quantum reactivity parameters. From natural bond orbital analysis, π* → π* is the major contributor to electron transition with the summation perturbation energy of 889.57 kcal/mol, while π → π* had the perturbation energy totaling of 145.3 kcal/mol. Geometry analysis shows BHANDH to have lower bond length values and lesser deviation from 120° in carbon-carbon angle. The potency of the title molecule as an asthma drug was tested via a molecular docking approach and the binding score of -8.2 kcal/mol was observed against -7.0 of salbutamol standard drug, suggesting romarinic acid as a potential natural organic treatment for asthma.Communicated by Ramaswamy H. Sarma.

Structural and pKa Estimation of the Amphipathic HR1 in SARS-CoV-2: Insights from Constant pH MD, Linear vs. Nonlinear Normal Mode Analysis

A comprehensive understanding of molecular interactions and functions is imperative for unraveling the intricacies of viral protein behavior and conformational dynamics during cellular entry. Focusing on the SARS-CoV-2 spike protein (SARS-CoV-2 sp), a Principal Component Analysis (PCA) on a subset comprising 131 A-chain structures in presence of various inhibitors was conducted. Our analyses unveiled a compelling correlation between PCA modes and Anisotropic Network Model (ANM) modes, underscoring the reliability and functional significance of low-frequency modes in adapting to diverse inhibitor binding scenarios. The role of HR1 in viral processing, both linear Normal Mode Analysis (NMA) and Nonlinear NMA were implemented. Linear NMA exhibited substantial inter-structure variability, as evident from a higher Root Mean Square Deviation (RMSD) range (7.30 Å), nonlinear NMA show stability throughout the simulations (RMSD 4.85 Å). Frequency analysis further emphasized that the energy requirements for conformational changes in nonlinear modes are notably lower compared to their linear counterparts. Using simulations of molecular dynamics at constant pH (cpH-MD), we successfully predicted the pKa order of the interconnected residues within the HR1 mutations at lower pH values, suggesting a transition to a post-fusion structure. The pKa determination study illustrates the profound effects of pH variations on protein structure. Key results include pKa values of 9.5179 for lys-921 in the D936H mutant, 9.50 for the D950N mutant, and a slightly higher value of 10.49 for the D936Y variant. To further understand the behavior and physicochemical characteristics of the protein in a biologically relevant setting, we also examine hydrophobic regions in the prefused states of the HR1 protein mutants D950N, D936Y, and D936H in our study. This analysis was conducted to ascertain the hydrophobic moment of the protein within a lipid environment, shedding light on its behavior and physicochemical properties in a biologically relevant context.

Computing Free Energies of Fold-Switching Proteins Using MELD x MD

Some proteins are conformational switches, able to transition between relatively different conformations. To understand what drives them requires computing the free-energy difference ΔGAB between their stable states, A and B. Molecular dynamics (MD) simulations alone are often slow because they require a reaction coordinate and must sample many transitions in between. Here, we show that modeling employing limited data (MELD) x MD on known endstates A and B is accurate and efficient because it does not require passing over barriers or knowing reaction coordinates. We validate this method on two problems: (1) it gives correct relative populations of α and β conformers for small designed chameleon sequences of protein G; and (2) it correctly predicts the conformations of the C-terminal domain (CTD) of RfaH. Free-energy methods like MELD x MD can often resolve structures that confuse machine-learning (ML) methods.

Unveiling the Anthelminthic Potential of Merremia vitifolia Stem through in Vitro and in Silico Approach

This study aimed to assess the anthelmintic activity of methanol extracts from Merremia vitifolia stems using a combination approach encompassing experimental, in vitro, and in silico evaluations. Despite the well-recognized pharmacological properties of M. vitifolia, its potential as an anthelmintic agent remained unexplored. This plant's anthelmintic potential was assessed on adult earthworms (Pheretima posthuma), revealing a dose-dependent reduction in spontaneous motility leading to paralysis and eventual mortality. The most effective dose of M. vitifolia (200 mg/ml) for anthelmintic effects on Pheretima posthuma was identified. Complementary in silico investigations were also conducted, employing Autodock PyRx 0.8 for docking studies of reported M. vitifolia compounds. Notably, quercetin emerged as a promising candidate with superior binding energies against β-tubulin (-8.3 Kcal/mol). Moreover, this comprehensive research underlines the anthelmintic potential of Merremia vitifolia stem extract and highlights quercetin as a noteworthy compound for further investigation in the quest for novel anthelmintic agents.

Scipion-EM-ProDy: A Graphical Interface for the ProDy Python Package within the Scipion Workflow Engine Enabling Integration of Databases, Simulations and Cryo-Electron Microscopy Image Processing

Macromolecular assemblies, such as protein complexes, undergo continuous structural dynamics, including global reconfigurations critical for their function. Two fast analytical methods are widely used to study these global dynamics, namely elastic network model normal mode analysis and principal component analysis of ensembles of structures. These approaches have found wide use in various computational studies, driving the development of complex pipelines in several software packages. One common theme has been conformational sampling through hybrid simulations incorporating all-atom molecular dynamics and global modes of motion. However, wide functionality is only available for experienced programmers with limited capabilities for other users. We have, therefore, integrated one popular and extensively developed software for such analyses, the ProDy Python application programming interface, into the Scipion workflow engine. This enables a wider range of users to access a complete range of macromolecular dynamics pipelines beyond the core functionalities available in its command-line applications and the normal mode wizard in VMD. The new protocols and pipelines can be further expanded and integrated into larger workflows, together with other software packages for cryo-electron microscopy image analysis and molecular simulations. We present the resulting plugin, Scipion-EM-ProDy, in detail, highlighting the rich functionality made available by its development.

Normal mode analysis and comparative study of intrinsic dynamics of alcohol oxidase enzymes from GMC protein family

Glucose-Methanol-Choline (GMC) family enzymes are very important in catalyzing the oxidation of a wide range of structurally diverse substrates. Enzymes that constitute the GMC family, share a common tertiary fold but < 25% sequence identity. Cofactor FAD, FAD binding signature motif, and similar structural scaffold of the active site are common features of oxidoreductase enzymes of the GMC family. Protein functionality mainly depends on protein three-dimensional structures and dynamics. In this study, we used the normal mode analysis method to search the intrinsic dynamics of GMC family enzymes. We have explored the dynamical behavior of enzymes with unique substrate catabolism and active site characteristics from different classes of the GMC family. Analysis of individual enzymes and comparative ensemble analysis of enzymes from different classes has shown conserved dynamic motion at FAD binding sites. The present study revealed that GMC enzymes share a strong dynamic similarity (Bhattacharyya coefficient >90% and root mean squared inner product >52%) despite low sequence identity across the GMC family enzymes. The study predicts that local deformation energy between atoms of the enzyme may be responsible for the catalysis of different substrates. This study may help that intrinsic dynamics can be used to make meaningful classifications of proteins or enzymes from different organisms.Communicated by Ramaswamy H. Sarma.

Interactions of the male contraceptive target EPPIN with semenogelin-1 and small organic ligands

Novel male contraceptives will promote gender equality in sharing contraceptive responsibility. The sperm-associated protein epididymal protease inhibitor (EPPIN) is a promising target for non-hormonal male contraception. EPPIN interacts with the semen coagulum protein semenogelin-1 (SEMG1) on the sperm surface, leading to transient inhibition of sperm motility after ejaculation. Small organic molecules targeting EPPIN's SEMG1-binding are under development as male contraceptives. Here, we combined computational approaches to uncover key aspects underlying EPPIN binding to SEMG1 and small organic ligands. We generated a human EPPIN model showing a typical arrangement of the WFDC (Whey-acid four disulfide core)-type and Kunitz-type domains, connected by a hinge region. Determining the EPPIN model's intrinsic motion by molecular dynamics simulations and normal mode analysis revealed a conformation, presenting a binding pocket that accommodates SEMG1Glu229-Gln247, EP055, and EP012. EPPIN's residues Phe63 and Lys68 (WFDC domain), Asp71 (hinge region), and Asn113, Asn114, and Asn115 (Kunitz domain) were identified as hot spots for SEMG1, EP055, and EP012 binding. Moreover, hydrophobic and hydrophilic residues in the WFDC and Kunitz domains allow plasma membrane anchoring, orienting the EPPIN binding pocket to the solvent. Targeting EPPIN's essential residues for its biomolecular interactions may improve the rational design of EPPIN ligands as spermiostatic compounds.

The stem region of group A transferase is crucial for its specificity, and its alteration promotes heterologous Forssman synthase activity

Some stem region mutants of human blood group A transferase (hAT) possess Forssman synthase (FS) activity, but very little is known about the mechanisms responsible for this enzymatic crosstalk. We performed confocal microscopy and image analysis to determine whether different intra-Golgi localization was accountable for this acquired activity. We also performed structural modeling and mutational and normal mode analyses. We introduced new mutations in the stem region and tested its FS and AT activities. No differences in subcellular localization were found between hAT and FS-positive mutants. AlphaFold models of hAT and mFS (mouse Forssman synthase) showed that the hAT stem region has a tether-like stem region, while in mFS, it encircles its catalytic domain. In silico analysis of FS-positive mutants indicated that stem region mutations induced structural changes, decreasing interatomic interactions and mobility of hAT that correlated with FS activity. Several additional mutations introduced in that region also bestowed FS activity without altering the AT activity: hAT 37-55 aa substitution by mFS 34-52, 37-55 aa deletion, and missense mutations: S46P, Q278Y, and Q286M. Stem region structure, mobility, and interactions are crucial for hAT specificity. Moreover, stem region mutations can lead to heterologous Forssman activity without changes in the catalytic machinery.

Characterizing interactions in E-cadherin assemblages

Cadherin intermolecular interactions are critical for cell-cell adhesion and play essential roles in tissue formation and the maintenance of tissue structures. In this study, we focus on E-cadherin, a classical cadherin that connects epithelial cells, to understand how they interact in cis and trans conformations when attached to the same cell or opposing cells. We employ coevolutionary sequence analysis and molecular dynamics simulations to confirm previously known interaction sites as well as to identify new interaction sites. The sequence coevolutionary results yield a surprising result indicating that there are no strongly favored intermolecular interaction sites, which is unusual and suggests that many interaction sites may be possible, with none being strongly preferred over others. By using molecular dynamics, we test the persistence of these interactions and how they facilitate adhesion. We build several types of cadherin assemblages, with different numbers and combinations of cis and trans interfaces to understand how these conformations act to facilitate adhesion. Our results suggest that, in addition to the established interaction sites on the EC1 and EC2 domains, an additional plausible cis interface at the EC3-EC5 domain exists. Furthermore, we identify specific mutations at cis/trans binding sites that impair adhesion within E-cadherin assemblages.

Defensin-based therapeutic peptide design in attenuating V30M TTR-induced Familial Amyloid Polyneuropathy

In the present study, we aimed to formulate an effective therapeutic candidate against V30M mutant transthyretin (TTR) protein to hinder its pathogenic misfolding. Nicotiana alata Defensin 1 (NaD1) Antimicrobial Peptide (AMP) was availed due to its tendency to aggregate, which may compete for aggregation-prone regions of pathogenic TTR protein. Based on NaD1's potential to bind to V30M TTR, we proposed NaD1-derived tetra peptides: CKTE and SKIL to be initial therapeutic candidates. Based on their association with mutant TTR protein, CKTE tetra peptide showed considerable interaction and curative potential as compared to SKIL tetra peptide. Further analyses from discrete molecular dynamics simulation corroborate CKTE tetra peptide's effectiveness as a 'beta-sheet breaker' against V30M TTR. Various post-simulation trajectory analyses suggested that CKTE tetra peptide alters the structural dynamics of pathogenic V30M TTR protein, thereby potentially attenuating its beta-sheets and impeding its aggregation. Normal mode analysis simulation corroborated that V30M TTR conformation is altered upon its interaction with CKTE peptide. Moreover, simulated thermal denaturation findings suggested that CKTE-V30M TTR complex is more susceptible to simulated denaturation, relative to pathogenic V30M TTR; further substantiating CKTE peptide's potential to alter V30M TTR's pathogenic conformation. Moreover, the residual frustration analysis augmented CKTE tetra peptide's proclivity in reorienting the conformation of V30M TTR. Therefore, we predicted that the tetra peptide, CKTE could be a promising therapeutic candidate in mitigating the amyloidogenic detrimental effects of V30M TTR-mediated familial amyloid polyneuropathy (FAP).

Supplementary Information

The online version contains supplementary material available at 10.1007/s13205-023-03646-4.

Microsecond Motion of the Bacterial Transporter EmrE in Lipid Bilayers

The bacterial transporter EmrE is a homo-dimeric membrane protein that effluxes cationic polyaromatic substrates against the concentration gradient by coupling to proton transport. As the archetype of the small multidrug resistance family of transporters, EmrE structure and dynamics provide atomic insights into the mechanism of transport by this family of proteins. We recently determined high-resolution structures of EmrE in complex with a cationic substrate, tetra(4-fluorophenyl)phosphonium (F4-TPP+), using solid-state NMR spectroscopy and an S64V-EmrE mutant. The substrate-bound protein exhibits distinct structures at acidic and basic pH, reflecting changes upon binding or release of a proton from residue E14, respectively. To obtain insight into the protein dynamics that mediate substrate transport, here we measure 15N rotating-frame spin-lattice relaxation (R1ρ) rates of F4-TPP+-bound S64V-EmrE in lipid bilayers under magic-angle spinning (MAS). Using perdeuterated and back-exchanged protein and 1H-detected 15N spin-lock experiments under 55 kHz MAS, we measured 15N R1ρ rates site-specifically. Many residues show spin-lock field-dependent 15N R1ρ relaxation rates. This relaxation dispersion indicates the presence of backbone motions at a rate of about 6000 s-1 at 280 K for the protein at both acidic and basic pH. This motional rate is 3 orders of magnitude faster than the alternating access rate but is within the range estimated for substrate binding. We propose that these microsecond motions may allow EmrE to sample different conformations to facilitate substrate binding and release from the transport pore.

Molecular Mechanisms of PTH/PTHrP Class B GPCR Signaling and Pharmacological Implications

The classical paradigm of G protein-coupled receptor (GPCR) signaling via G proteins is grounded in a view that downstream responses are relatively transient and confined to the cell surface, but this notion has been revised in recent years following the identification of several receptors that engage in sustained signaling responses from subcellular compartments following internalization of the ligand-receptor complex. This phenomenon was initially discovered for the parathyroid hormone (PTH) type 1 receptor (PTH1R), a vital GPCR for maintaining normal calcium and phosphate levels in the body with the paradoxical ability to build or break down bone in response to PTH binding. The diverse biological processes regulated by this receptor are thought to depend on its capacity to mediate diverse modes of cyclic adenosine monophosphate (cAMP) signaling. These include transient signaling at the plasma membrane and sustained signaling from internalized PTH1R within early endosomes mediated by PTH. Here we discuss recent structural, cell signaling, and in vivo studies that unveil potential pharmacological outputs of the spatial versus temporal dimension of PTH1R signaling via cAMP. Notably, the combination of molecular dynamics simulations and elastic network model-based methods revealed how precise modulation of PTH signaling responses is achieved through structure-encoded allosteric coupling within the receptor and between the peptide hormone binding site and the G protein coupling interface. The implications of recent findings are now being explored for addressing key questions on how location bias in receptor signaling contributes to pharmacological functions, and how to drug a difficult target such as the PTH1R toward discovering nonpeptidic small molecule candidates for the treatment of metabolic bone and mineral diseases.

Mechanism of Allosteric Modulation of Nicotinamide Phosphoribosyltransferase to Elevate Cellular NAD. Biochemistry 2023;62:923-933. [PMID: 36746631 DOI: 10.1021/acs.biochem.2c00655]

In aging and disease, cellular nicotinamide adenine dinucleotide (NAD+) is depleted by catabolism to nicotinamide (NAM). NAD+ supplementation is being pursued to enhance human healthspan and lifespan. Activation of nicotinamide phosphoribosyltransferase (NAMPT), the rate-limiting step in NAD+ biosynthesis, has the potential to increase the salvage of NAM. Novel NAMPT-positive allosteric modulators (N-PAMs) were discovered in addition to the demonstration of NAMPT activation by biogenic phenols. The mechanism of activation was revealed through the synthesis of novel chemical probes, new NAMPT co-crystal structures, and enzyme kinetics. Binding to a rear channel in NAMPT regulates NAM binding and turnover, with biochemical observations being replicated by NAD+ measurements in human cells. The mechanism of action of N-PAMs identifies, for the first time, the role of the rear channel in the regulation of NAMPT turnover coupled to productive and nonproductive NAM binding. The tight regulation of cellular NAMPT via feedback inhibition by NAM, NAD+, and adenosine 5'-triphosphate (ATP) is differentially regulated by N-PAMs and other activators, indicating that different classes of pharmacological activators may be engineered to restore or enhance NAD+ levels in affected tissues.

Phylogenetic, structural, functional characterisation and effect of exogenous spermidine on rice (Oryza sativa) HAK transporters under salt stress

The HAK (High-affinity K+ ) family members mediate K+ transport that confers normal plant growth and resistance against unfavourable environmental conditions. Rice (Oryza sativa L.) HAK transporters have been extensively investigated for phylogenetic analyses with other plants species with very few of them functionally characterised. But very little information is known about their evolutionary aspects, overall structural, functional characterisation, and global expression pattern of the complete HAK family members in response to salt stress. In this study, 27 rice transporters were phylogenetically clustered with different dicot and monocot family members. Subsequently, the exon-intron structural patterns, conserved motif analyses, evolutionary divergence based different substitution matrix, orthologous-paralogous relationships were studied elaborately. Structural characterisations included a comparative study of secondary and tertiary structure, post-translational modifications, correspondence analyses, normal mode analyses, K+ /Na+ binding affinities of each of the OsHAK gene members. Global expression profile under salt stress showed clade-specific expression pattern of the proteins. Additionally, five OsHAK genes were chosen for further expression analyses in root and shoot tissues of two rice varieties during short-term salinity in the presence and absence of exogenous spermidine. All the information can be used as first-hand data for dissecting the administrative role of rice HAK transporters under various abiotic stresses.

Toward Reliable and Insightful Entropy Calculations on Flexible Molecules

The absolute entropy of a flexible molecule can be approximated by the sum of a rigid-rotor-harmonic-oscillator (RRHO) entropy and a Gibbs-Shannon entropy associated to the Boltzmann distribution for the occupation of the conformational energy levels. Herein, we show that such partitioning, which has received renewed interest, leads to accurate entropies of single molecules of increasing size provided that the conformational part is estimated by means of a set of discretization and expansion techniques that are able to capture the significant correlation effects among the torsional motions. To ensure a reliable entropy estimation, we rely on extensive sampling as that produced by classical molecular dynamics simulations on the microsecond time scale, which is currently affordable for small- and medium-sized molecules. According to test calculations, the gas-phase entropy of simple organic molecules is predicted with a mean unsigned error of 0.9 cal/(mol K) when the RRHO entropies are computed at the B3LYP-D3/cc-pVTZ level. Remarkably, the same protocol gives small errors [<1 cal/(mol K)] for the extremely flexible linear alkane molecules (C_nH_2n+2, n = 14, 16, and 18). Similarly, we obtain well-converged entropies for a more challenging test of drug molecules, which exhibit more pronounced correlation effects. We also perform equivalent entropy calculations on a 76 amino acid protein, ubiquitin, by taking advantage of the cutoff-dependent formulation of an expansion technique (correlation-consistent multibody local approximation, CC-MLA), which incorporates genuine correlation effects among the neighboring dihedral angles. Moreover, we show that insightful descriptors of the coupled torsional motions can be obtained with the CC-MLA approach.

Evolutionary adaptation of the protein folding pathway for secretability

Secretory preproteins of the Sec pathway are targeted post-translationally and cross cellular membranes through translocases. During cytoplasmic transit, mature domains remain non-folded for translocase recognition/translocation. After translocation and signal peptide cleavage, mature domains fold to native states in the bacterial periplasm or traffic further. We sought the structural basis for delayed mature domain folding and how signal peptides regulate it. We compared how evolution diversified a periplasmic peptidyl-prolyl isomerase PpiA mature domain from its structural cytoplasmic PpiB twin. Global and local hydrogen-deuterium exchange mass spectrometry showed that PpiA is a slower folder. We defined at near-residue resolution hierarchical folding initiated by similar foldons in the twins, at different order and rates. PpiA folding is delayed by less hydrophobic native contacts, frustrated residues and a β-turn in the earliest foldon and by signal peptide-mediated disruption of foldon hierarchy. When selected PpiA residues and/or its signal peptide were grafted onto PpiB, they converted it into a slow folder with enhanced in vivo secretion. These structural adaptations in a secretory protein facilitate trafficking.

Exploring the multiple conformational states of RNA genome through interhelical dynamics and network analysis

The structural variation of RNA is often very transient and can be easily missed in experiments. Molecular dynamics simulation studies along with network analysis can be an effective tool to identify prominent conformations of such dynamic biomolecular systems. Here we describe a method to effectively sample different RNA conformations at six different temperatures based on the changes in the interhelical orientations. This method gives the information about prominent states of the RNA as well as the probability of the existence of different conformations and their interconnections during the process of evolution. In the case of the SARS-CoV-2 genome, the change of prominent structures was found to be faster at 333 K as compared to higher temperatures due to the formation of the non-native base pairs. ΔΔG calculated between 288 K and 363 K are found to be 10.31 kcal/mol (88 nt) considering the contribution from the multiple states of the RNA which agrees well with the experimentally reported denaturation energy for E. coli α mRNA pseudoknot (∼16 kcal/mol, 112 nt) determined by calorimetry/UV hyperchromicity and human telomerase RNA telomerase (4.5-6.6 kcal/mol, 54 nt) determined by FRET analysis.

Conformational Stability and Denaturation Processes of Proteins Investigated by Electrophoresis under Extreme Conditions

The functional structure of proteins results from marginally stable folded conformations. Reversible unfolding, irreversible denaturation, and deterioration can be caused by chemical and physical agents due to changes in the physicochemical conditions of pH, ionic strength, temperature, pressure, and electric field or due to the presence of a cosolvent that perturbs the delicate balance between stabilizing and destabilizing interactions and eventually induces chemical modifications. For most proteins, denaturation is a complex process involving transient intermediates in several reversible and eventually irreversible steps. Knowledge of protein stability and denaturation processes is mandatory for the development of enzymes as industrial catalysts, biopharmaceuticals, analytical and medical bioreagents, and safe industrial food. Electrophoresis techniques operating under extreme conditions are convenient tools for analyzing unfolding transitions, trapping transient intermediates, and gaining insight into the mechanisms of denaturation processes. Moreover, quantitative analysis of electrophoretic mobility transition curves allows the estimation of the conformational stability of proteins. These approaches include polyacrylamide gel electrophoresis and capillary zone electrophoresis under cold, heat, and hydrostatic pressure and in the presence of non-ionic denaturing agents or stabilizers such as polyols and heavy water. Lastly, after exposure to extremes of physical conditions, electrophoresis under standard conditions provides information on irreversible processes, slow conformational drifts, and slow renaturation processes. The impressive developments of enzyme technology with multiple applications in fine chemistry, biopharmaceutics, and nanomedicine prompted us to revisit the potentialities of these electrophoretic approaches. This feature review is illustrated with published and unpublished results obtained by the authors on cholinesterases and paraoxonase, two physiologically and toxicologically important enzymes.

Optimising Elastic Network Models for Protein Dynamics and Allostery: Spatial and Modal Cut-offs and Backbone Stiffness

The family of coarse-grained models for protein dynamics known as Elastic Network Models (ENMs) require careful choice of parameters to represent well experimental measurements or fully-atomistic simulations. The most basic ENM that represents each protein residue by a node at the position of its C-alpha atom, all connected by springs of equal stiffness, up to a cut-off in distance. Even at this level a choice is required of the optimum cut-off distance and the upper limit of elastic normal modes taken in any sum for physical properties, such as dynamic correlation or allosteric effects on binding. Additionally, backbone-enhanced ENM (BENM) may improve the model by allocating a higher stiffness to springs that connect along the protein backbone. This work reports on the effect of varying these three parameters (distance and mode cutoffs, backbone stiffness) on the dynamical structure of three proteins, Catabolite Activator Protein (CAP), Glutathione S-transferase (GST), and the SARS-CoV-2 Main Protease (M pro ). Our main results are: (1) balancing B-factor and dispersion-relation predictions, a near-universal optimal value of 8.5 Å is advisable for ENMs; (2) inhomogeneity in elasticity brings the first mode containing spatial structure not well-resolved by the ENM typically within the first 20; (3) the BENM only affects modes in the upper third of the distribution, and, additionally to the ENM, is only able to model the dispersion curve better in this vicinity; (4) BENM does not typically affect fluctuation-allostery, which also requires careful treatment of the effector binding to the host protein to capture.

Exploring the Conformational Impact of Glycine Receptor TM1-2 Mutations Through Coarse-Grained Analysis and Atomistic Simulations

Pentameric ligand-gated ion channels (PLGICs) are a family of proteins that convert chemical signals into ion fluxes through cellular membranes. Their structures are highly conserved across all kingdoms from bacteria to eukaryotes. Beyond their classical roles in neurotransmission and neurological disorders, PLGICs have been recently related to cell proliferation and cancer. Here, we focus on the best characterized eukaryotic channel, the glycine receptor (GlyR), to investigate its mutational patterns in genomic-wide tumor screens and compare them with mutations linked to hyperekplexia (HPX), a Mendelian neuromotor disease that disrupts glycinergic currents. Our analysis highlights that cancer mutations significantly accumulate across TM1 and TM2, partially overlapping with HPX changes. Based on 3D-clustering, conservation, and phenotypic data, we select three mutations near the pore, expected to impact GlyR conformation, for further study by molecular dynamics (MD). Using principal components from experimental GlyR ensembles as framework, we explore the motions involved in transitions from the human closed and desensitized structures and how they are perturbed by mutations. Our MD simulations show that WT GlyR spontaneously explores opening and re-sensitization transitions that are significantly impaired by mutations, resulting in receptors with altered permeability and desensitization properties in agreement with HPX functional data.

Altered Dynamics of S. aureus Phosphofructokinase via Bond Restraints at Two Distinct Allosteric Binding Sites

The effect of perturbation at the allosteric site was investigated through several replicas of molecular dynamics (MD) simulations conducted on bacterial phosphofructokinase (SaPFK). In our previous work, an alternative binding site was estimated to be allosteric in addition to the experimentally reported one. To highlight the effect of both allosteric sites on receptor's dynamics, MD runs were carried out on apo forms with and without perturbation. Perturbation was achieved via incorporating multiple bond restraints for residue pairs located at the allosteric site. Restraints applied to the predicted site caused one dimer to stiffen, whereas an increase in mobility was detected in the same dimer when the experimentally resolved site was restrained. Fluctuations in C_α-C_α distances which is used to disclose residues with high potential of communication indicated a marked increase in signal transmission within each dimer as the receptor switched to a restrained state. Cross-correlation of positional fluctuations indicated an overall decrease in the magnitude of both positive and negative correlations when restraints were employed on the predicted allosteric site whereas an exact opposite effect was observed for the reported site. Finally, mutual correspondence between positional fluctuations noticeably increased with restraints on predicted allosteric site, whereas an opposite effect was observed for restraints applied on experimentally reported one. In view of these findings, it is clear that the perturbation of either one of two allosteric sites effected the dynamics of the receptor with a distinct and contrasting character.

Epithelial Sodium Channel Inhibition by Amiloride Addressed with THz Spectroscopy and Molecular Modeling

THz spectroscopy is important for the study of ion channels because it directly addresses the low frequency collective motions relevant for their function. Here we used THz spectroscopy to investigate the inhibition of the epithelial sodium channel (ENaC) by its specific blocker, amiloride. Experiments were performed on A6 cells' suspensions, which are cells overexpressing ENaC derived from Xenopus laevis kidney. THz spectra were investigated with or without amiloride. When ENaC was inhibited by amiloride, a substantial increase in THz absorption was noticed. Molecular modeling methods were used to explain the observed spectroscopic differences. THz spectra were simulated using the structural models of ENaC and ENaC-amiloride complexes built here. The agreement between the experiment and the simulations allowed us to validate the structural models and to describe the amiloride dynamics inside the channel pore. The amiloride binding site validated using THz spectroscopy agrees with previous mutagenesis studies. Altogether, our results show that THz spectroscopy can be successfully used to discriminate between native and inhibited ENaC channels and to characterize the dynamics of channels in the presence of their specific antagonist.

Computation of the Protein Conformational Transition Pathway on Ligand Binding by Linear Response-Driven Molecular Dynamics

While extremely important for relating the protein structure to its biological function, determination of the protein conformational transition pathway upon ligand binding is made difficult due to the transient nature of intermediates, a large and rugged conformational space, and coupling between protein dynamics and ligand-protein interactions. Existing methods that rely on prior knowledge of the bound (holo) state structure are restrictive. A second concern relates to the correspondence of intermediates obtained to the metastable states on the apo → holo transition pathway. Here, we have taken the protein apo structure and ligand-binding site as only inputs and combined an elastic network model (ENM) representation of the protein Hamiltonian with linear response theory (LRT) for protein-ligand interactions to identify the set of slow normal modes of protein vibrations that have a high overlap with the direction of the protein conformational change. The structural displacement along the chosen direction was performed using excited normal modes molecular dynamics (MDeNM) simulations rather than by the direct use of LRT. Herein, the MDeNM excitation velocity was optimized on-the-fly on the basis of its coupling to protein dynamics and ligand-protein interactions. Thus, a determined set of structures was validated against crystallographic and simulation data on four protein-ligand systems, namely, adenylate kinase-di(adenosine-5')pentaphosphate, ribose binding protein-β-d-ribopyranose, DNA β-glucosyltransferase-uridine-5'-diphosphate, and G-protein α subunit-guanosine-5'-triphosphate, which present important differences in protein conformational heterogeneity, ligand binding mechanism, viz. induced-fit or conformational selection, extent, and nonlinearity in protein conformational changes upon ligand binding, and presence of allosteric effects. The obtained set of intermediates was used as an input to path metadynamics simulations to obtain the free energy profile for the apo → holo transition.

High-pressure crystallography shows noble gas intervention into protein-lipid interaction and suggests a model for anaesthetic action

In this work we examine how small hydrophobic molecules such as inert gases interact with membrane proteins (MPs) at a molecular level. High pressure atmospheres of argon and krypton were used to produce noble gas derivatives of crystals of three well studied MPs (two different proton pumps and a sodium light-driven ion pump). The structures obtained using X-ray crystallography showed that the vast majority of argon and krypton binding sites were located on the outer hydrophobic surface of the MPs – a surface usually accommodating hydrophobic chains of annular lipids (which are known structural and functional determinants for MPs). In conformity with these results, supplementary in silico molecular dynamics (MD) analysis predicted even greater numbers of argon and krypton binding positions on MP surface within the bilayer. These results indicate a potential importance of such interactions, particularly as related to the phenomenon of noble gas-induced anaesthesia.

Noble gases are known to interact with proteins and can be good anaesthetics in hyperbaric conditions. This study identifies argon and krypton binding sites on membrane proteins and proposes as a hypothesis that noble gases, by altering protein/lipid contacts, may affect protein function.

In Silico and In Vitro Evaluations of Fluorophoric Thiazolo-[2,3-b]quinazolinones as Anti-cancer Agents Targeting EGFR-TKD

Epidermal growth factor receptor tyrosine kinase domain (EGFR-TKD) plays a pivotal role in cellular signaling, growth, and metabolism. The EGFR-TKD is highly expressed in cancer cells and was endorsed as a therapeutic target for cancer management to overcome metastasis, cell proliferation, and angiogenesis. The novel thiazolo-[2,3-b]quinazolinones series were strategically developed by microwave-assisted organic synthesis and multi dominos reactions aimed to identify the potent thiazolo-[2,3-b]quinazolinone inhibitor against EGFR-TKD. This study explores the binding stability and binding strength of newly developed series via molecular docking, molecular dynamics simulation, and MM/PBSA and MM/GBSA calculations. The binding interaction was observed to be through the functional groups on aryl substituents at positions 3 and 5 of the thiazolo-[2, 3-b]quinazolinone scaffold. The methyl substituents at position 8 of the ligands had prominent hydrophobic interactions corroborating their bindings similar to the reference FDA-approved drug erlotinib in the active site. ADMET predictions reveal that derivatives 5ab, 5aq, and 5bq are drug-like and may be effective in in vitro study. Molecular dynamics simulation for 100 ns of docked complexes revealed their stability at the atomistic level. The ΔGbinding of thiazolo-[2,3-b]quinazolinone was found to be 5ab - 22.45, 5aq - 22.23, and 5bq - 20.76 similar to standard drug, and erlotinib - 24.11 kcal/mol was determined by MM/GBSA method. Furthermore, the anti-proliferative activity of leads of thiazolo-[2,3-b]quinazolinones (n = 3) was studied against breast cancer cell line (MCF-7) and non-small lung carcinoma cell line (H-1299). The highest inhibitions in cell proliferation were shown by 5bq derivatives, and the IC₅₀ was found to be 6.5 ± 0.67 µM against MCF-7 and 14.8 µM against H-1299. The noscapine was also taken as a positive control and showed IC₅₀ at higher concentrations 37 ± 1 against MCF-7 and 46.5 ± 1.2 against H-1299.

Protein dynamics developments for the large scale and cryoEM: case study of ProDy 2.0

Cryo-electron microscopy (cryoEM) has become a well established technique with the potential to produce structures of large and dynamic supramolecular complexes that are not amenable to traditional approaches for studying structure and dynamics. The size and low resolution of such molecular systems often make structural modelling and molecular dynamics simulations challenging and computationally expensive. This, together with the growing wealth of structural data arising from cryoEM and other structural biology methods, has driven a trend in the computational biophysics community towards the development of new pipelines for analysing global dynamics using coarse-grained models and methods. At the centre of this trend has been a return to elastic network models, normal mode analysis (NMA) and ensemble analyses such as principal component analysis, and the growth of hybrid simulation methodologies that make use of them. Here, this field is reviewed with a focus on ProDy, the Python application programming interface for protein dynamics, which has been developed over the last decade. Two key developments in this area are highlighted: (i) ensemble NMA towards extracting and comparing the signature dynamics of homologous structures, aided by the recent SignDy pipeline, and (ii) pseudoatom fitting for more efficient global dynamics analyses of large and low-resolution supramolecular assemblies from cryoEM, revisited in the CryoDy pipeline. It is believed that such a renewal and extension of old models and methods in new pipelines will be critical for driving the field forward into the next cryoEM revolution.

Structure-mechanics statistical learning uncovers mechanical relay in proteins

A protein's adaptive response to its substrates is one of the key questions driving molecular physics and physical chemistry. This work employs the recently developed structure-mechanics statistical learning method to establish a mechanical perspective. Specifically, by mapping all-atom molecular dynamics simulations onto the spring parameters of a backbone-side-chain elastic network model, the chemical moiety specific force constants (or mechanical rigidity) are used to assemble the rigidity graph, which is the matrix of inter-residue coupling strength. Using the S1A protease and the PDZ3 signaling domain as examples, chains of spatially contiguous residues are found to exhibit prominent changes in their mechanical rigidity upon substrate binding or dissociation. Such a mechanical-relay picture thus provides a mechanistic underpinning for conformational changes, long-range communication, and inter-domain allostery in both proteins, where the responsive mechanical hotspots are mostly residues having important biological functions or significant mutation sensitivity.

Protein residues exhibit specific routes of mechanical relay as the adaptive responses to substrate binding or dissociation. On such physically contiguous connections, residues experience prominent changes in their coupling strengths.

Molecular Modeling is an Enabling Approach to Complement and Enhance Channelopathy Research

Hundreds of human membrane proteins form channels that transport necessary ions and compounds, including drugs and metabolites, yet details of their normal function or how function is altered by genetic variants to cause diseases are often unknown. Without this knowledge, researchers are less equipped to develop approaches to diagnose and treat channelopathies. High-resolution computational approaches such as molecular modeling enable researchers to investigate channelopathy protein function, facilitate detailed hypothesis generation, and produce data that is difficult to gather experimentally. Molecular modeling can be tailored to each physiologic context that a protein may act within, some of which may currently be difficult or impossible to assay experimentally. Because many genomic variants are observed in channelopathy proteins from high-throughput sequencing studies, methods with mechanistic value are needed to interpret their effects. The eminent field of structural bioinformatics integrates techniques from multiple disciplines including molecular modeling, computational chemistry, biophysics, and biochemistry, to develop mechanistic hypotheses and enhance the information available for understanding function. Molecular modeling and simulation access 3D and time-dependent information, not currently predictable from sequence. Thus, molecular modeling is valuable for increasing the resolution with which the natural function of protein channels can be investigated, and for interpreting how genomic variants alter them to produce physiologic changes that manifest as channelopathies. © 2022 American Physiological Society. Compr Physiol 12:3141-3166, 2022.

Response of Terahertz Protein Vibrations to Ligand Binding: Calmodulin-Peptide Complexes as a Case Study

Terahertz vibrations are sensitive reporters of the structure and interactions of proteins. Ligand binding alters the nature and distribution of these collective vibrations. The ligand-induced changes in the terahertz protein vibrations contribute to the binding entropy and to the overall thermodynamic stability of the resultant protein-ligand complexes. Here, we have examined the response of the low-frequency (below 6 terahertz) collective vibrations of the calcium-loaded calmodulin (CaM) to binding to five different ligands, both in the presence and absence of water, using normal-mode analysis and molecular dynamics simulations. A comparison of the vibrational spectra of hydrated and dry systems reveals that protein-solvent interactions stiffen the terahertz protein vibrations and that these solvent-coupled collective vibrations contribute significantly to the hydration-sensitive variation in the vibrational entropy of CaM. In the absence of water, the low-frequency vibrations of CaM are stiffened by ligand binding. On the contrary, the number and the cumulative vibrational entropy of low-frequency vibrational modes (ω < 200 cm^-1) of the hydrated CaM are increased noticeably after binding to the peptides, indicating binding-induced softening of collective vibrations of the protein. Although the calculated and experimental binding affinities of the chosen complexes correlated reasonably well, no systematic correlation was observed between the protein vibrational entropy and the binding affinity. The results underscored the importance of the interplay of protein-ligand and solvent interactions in modulating the low-frequency vibrations of proteins.

Exploring nature's bounty: identification of Withania somnifera as a promising source of therapeutic agents against COVID-19 by virtual screening and in silico evaluation

Coronaviruses are etiological agents of extreme human and animal infection resulting in abnormalities primarily in the respiratory tract. Presently, there is no defined COVID-19 intervention and clinical trials of prospective therapeutic agents are still in the nascent stage. Withania somnifera (L.) Dunal (WS), is an important medicinal plant in Ayurveda. The present study aimed to evaluate the antiviral potential of selected WS phytoconstituents against the novel SARS-CoV-2 target proteins and human ACE2 receptor using in silico methods. Most of the phytoconstituents displayed good absorption and transport kinetics and were also found to display no associated mutagenic or adverse effect(s). Molecular docking analyses revealed that most of the WS phytoconstituents exhibited potent binding to human ACE2 receptor, SAR-CoV and SARS-CoV-2 spike glycoproteins as well as the two main SARS-CoV-2 proteases. Most of the phytoconstituents were predicted to undergo Phase-I metabolism prior to excretion. All phytoconstituents had favorable bioactivity scores with respect to various receptor proteins and target enzymes. SAR analysis revealed that the number of oxygen atoms in the withanolide backbone and structural rearrangements were crucial for effective binding. Molecular simulation analyses of SARS-CoV-2 spike protein and papain-like protease with Withanolides A and B, respectively, displayed a stability profile at 300 K and constant RMSDs of protein side chains and Cα atoms throughout the simulation run time. In a nutshell, WS phytoconstituents warrant further investigations in vitro and in vivo to unravel their molecular mechanism(s) and modes of action for their future development as novel antiviral agents against COVID-19.

Optimized Elastic Network Models With Direct Characterization of Inter-Residue Cooperativity for Protein Dynamics

The elastic network models (ENMs)are known as representative coarse-grained models to capture essential dynamics of proteins. Due to simple designs of the force constants as a decay with spatial distances of residue pairs in many previous studies, there is still much room for the improvement of ENMs. In this article, we directly computed the force constants with the inverse covariance estimation using a ridge-type operater for the precision matrix estimation (ROPE)on a large-scale set of NMR ensembles. Distance-dependent statistical analyses on the force constants were further comprehensively performed in terms of several paired types of sequence and structural information, including secondary structure, relative solvent accessibility, sequence distance and terminal. Various distinguished distributions of the mean force constants highlight the structural and sequential characteristics coupled with the inter-residue cooperativity beyond the spatial distances. We finally integrated these structural and sequential characteristics to build novel ENM variations using the particle swarm optimization for the parameter estimation. The considerable improvements on the correlation coefficient of the mean-square fluctuation and the mode overlap were achieved by the proposed variations when compared with traditional ENMs. This study opens a novel way to develop more accurate elastic network models for protein dynamics.

SARS-CoV-2 Spike Protein Unlikely to Bind to Integrins via the Arg-Gly-Asp (RGD) Motif of the Receptor Binding Domain: Evidence From Structural Analysis and Microscale Accelerated Molecular Dynamics

The Receptor Binding Domain (RBD) of SARS-CoV-2 virus harbors a sequence of Arg-Gly-Asp tripeptide named RGD motif, which has also been identified in extracellular matrix proteins that bind integrins as well as other disintegrins and viruses. Accordingly, integrins have been proposed as host receptors for SARS-CoV-2. However, given that the microenvironment of the RGD motif imposes a structural hindrance to the protein-protein association, the validity of this hypothesis is still uncertain. Here, we used normal mode analysis, accelerated molecular dynamics microscale simulation, and protein-protein docking to investigate the putative role of RGD motif of SARS-CoV-2 RBD for interacting with integrins. We found, that neither RGD motif nor its microenvironment showed any significant conformational shift in the RBD structure. Highly populated clusters of RBD showed no capability to interact with the RGD binding site in integrins. The free energy landscape revealed that the RGD conformation within RBD could not acquire an optimal geometry to allow the interaction with integrins. In light of these results, and in the event where integrins are confirmed to be host receptors for SARS-CoV-2, we suggest a possible involvement of other residues to stabilize the interaction.

A Comparative Evaluation of the Structural and Dynamic Properties of Insect Odorant Binding Proteins

Insects devote a major part of their metabolic resources to the production of odorant binding proteins (OBPs). Although initially, these proteins were implicated in the solubilisation, binding and transport of semiochemicals to olfactory receptors, it is now recognised that they may play diverse, as yet uncharacterised, roles in insect physiology. The structures of these OBPs, the majority of which are known as “classical” OBPs, have shed some light on their potential functional roles. However, the dynamic properties of these proteins have received little attention despite their functional importance. Structural dynamics are encoded in the native protein fold and enable the adaptation of proteins to substrate binding. This paper provides a comparative review of the structural and dynamic properties of OBPs, making use of sequence/structure analysis, statistical and theoretical physics-based methods. It provides a new layer of information and additional methodological tools useful in unravelling the relationship between structure, dynamics and function of insect OBPs. The dynamic properties of OBPs, studied by means of elastic network models, reflect the similarities/dissimilarities observed in their respective structures and provides insights regarding protein motions that may have important implications for ligand recognition and binding. Furthermore, it was shown that the OBPs studied in this paper share conserved structural ‘core’ that may be of evolutionary and functional importance.