Dynamical networks in tRNA:protein complexes

Conformational plasticity of SpyCas9 induced by AcrIIA4 and AcrIIA2: Insights from molecular dynamics simulation

CRISPR-Cas9 systems constitute bacterial adaptive immune systems that protect against phage infections. Bacteriophages encode anti-CRISPR proteins (Acrs) that mitigate the bacterial immune response. However, the structural basis for their inhibitory actions from a molecular perspective remains elusive. In this study, through microsecond atomistic molecular dynamics simulations, we demonstrated the remarkable flexibility of Streptococcus pyogenes Cas9 (SpyCas9) and its conformational adaptability during interactions with AcrIIA4 and AcrIIA2. Specifically, we demonstrated that the binding of AcrIIA4 and AcrIIA2 to SpyCas9 induces a conformational rearrangement that causes spatial separation between the nuclease and cleavage sites, thus making the endonuclease inactive. This separation disrupts the transmission of signals between the protospacer adjacent motif recognition and nuclease domains, thereby impeding the efficient processing of double-stranded DNA. The simulation also reveals that AcrIIA4 and AcrIIA2 cause different structural variations of SpyCas9. Our research illuminates the precise mechanisms underlying the suppression of SpyCas9 by AcrIIA4 and AcrIIA2, thus presenting new possibilities for controlling genome editing with higher accuracy.

Mechanistic insights into the allosteric inactivation mechanism of ZAP-70 induced by the hot spot W165C mutation

Zeta chain-associated protein kinase 70 (ZAP-70) is a non-receptor tyrosine kinase that interacts with the activated T-cell receptor to transduce downstream signals, and thus plays an important role in the adaptive immune system. The biphosphorylated immunotyrosine-based activation motifs (ITAM-Y2P) binds to the N-SH2 and C-SH2 domains of ZAP-70 to promote the activation of ZAP-70. The present study explores molecular mechanisms of allosteric inactivation of ZAP-70 induced by the hot spot W165C mutation through atomically detailed molecular dynamics simulation approaches. We report microsecond-length simulations of two states of the tandem SH2 domains of ZAP-70 in complex with the ITAM-Y2P motif, including the wild-type and W165C mutant. Extensive analysis of local flexibility and dynamical correlated motions show that W165C mutation changes coupled motions of protein domains and community networks. The binding affinities of the ITAM-Y2P motif to the wild-type and W165C mutant of ZAP-70 are predicted using binding free energy calculations. The results suggest that the driving force to decrease the binding affinity in the W165C mutant derives from the difference in the protein-protein electrostatic interactions. Moreover, the per-residue free energy decomposition unravels that the contributions from residues in the phosphorylated Tyr315 (pY315) binding site, in particular pY315 of ITAM-Y2P, and Arg43, Tyr240 of ZAP-70, are the key determinants for the loss of binding affinity. This study may insights into our understanding of the pathological mechanism of ZAP-70.Communicated by Ramaswamy H. Sarma.

Accurate estimation of the normalized mutual information of multidimensional data

While the linear Pearson correlation coefficient represents a well-established normalized measure to quantify the inter-relation of two stochastic variables X and Y, it fails for multidimensional variables, such as Cartesian coordinates. Avoiding any assumption about the underlying data, the mutual information I(X, Y) does account for multidimensional correlations. However, unlike the normalized Pearson correlation, it has no upper bound (I ∈ [0, ∞)), i.e., it is not clear if say, I = 0.4 corresponds to a low or a high correlation. Moreover, the mutual information (MI) involves the estimation of high-dimensional probability densities (e.g., six-dimensional for Cartesian coordinates), which requires a k nearest-neighbor algorithm, such as the estimator by Kraskov et al. [Phys. Rev. E 69, 066138 (2004)]. As existing methods to normalize the MI cannot be used in connection with this estimator, a new approach is presented, which uses an entropy estimation method that is invariant under variable transformations. The algorithm is numerically efficient and does not require more effort than the calculation of the (un-normalized) MI. After validating the method by applying it to various toy models, the normalized MI between the Cα-coordinates of T4 lysozyme is considered and compared to a correlation analysis of inter-residue contacts.

Oncogenic R248W mutation induced conformational perturbation of the p53 core domain and the structural protection by proteomimetic amyloid inhibitor ADH-6

The involvement of p53 aggregation in cancer pathogenesis emphasizes the importance of unraveling the mechanisms underlying mutation-induced p53 destabilization. And understanding how small molecule inhibitors prevent the conversion of p53 into aggregation-primed conformations is pivotal for the development of therapeutics targeting p53-aggregation-associated cancers. A recent experimental study highlights the efficacy of the proteomimetic amyloid inhibitor ADH-6 in stabilizing R248W p53 and inhibiting its aggregation in cancer cells by interacting with the p53 core domain (p53C). However, it remains mostly unclear how R248W mutation induces destabilization of p53C and how ADH-6 stabilizes this p53C mutant and inhibits its aggregation. Herein, we conducted all-atom molecular dynamics simulations of R248W p53C in the absence and presence of ADH-6, as well as that of wild-type (WT) p53C. Our simulations reveal that the R248W mutation results in a shift of helix H2 and β-hairpin S2-S2' towards the mutation site, leading to the destruction of their neighboring β-sheet structure. This further facilitates the formation of a cavity in the hydrophobic core, and reduces the stability of the β-sandwich. Importantly, two crucial aggregation-prone regions (APRs) S9 and S10 are disturbed and more exposed to solvent in R248W p53C, which is conducive to p53C aggregation. Intriguingly, ADH-6 dynamically binds to the mutation site and multiple destabilized regions in R248W p53C, partially inhibiting the shift of helix H2 and β-hairpin S2-S2', thus preventing the disruption of the β-sheets and the formation of the cavity. ADH-6 also reduces the solvent exposure of APRs S9 and S10, which disfavors the aggregation of R248W p53C. Moreover, ADH-6 can preserve the WT-like dynamical network of R248W p53C. Our study elucidates the mechanisms underlying the oncogenic R248W mutation induced p53C destabilization and the structural protection of p53C by ADH-6.

A highly specific aptamer for the SARS-CoV-2 spike protein from the authentic strain

DNA aptamers are oligonucleotides that specifically bind to target molecules, similar to how antibodies bind to antigens. We identified an aptamer named MEZ that is highly specific to the receptor-binding domain, RBD, of the SARS-CoV-2 spike protein from the Wuhan-Hu-1 strain. The SELEX procedure was utilized to enrich the initial 31-mer oligonucleotide library with the target aptamer. The aptamer identification was performed using the novel protocol based on nanopore sequencing developed in this study. The MEZ aptamer was chemically synthesized and tested for binding with the SARS-CoV-2 RBD of the spike protein from different strains. The Kd is 6.5 nM for the complex with the RBD from the Wuhan-Hu-1 strain, which is comparable with known aptamers; the advantage is that the MEZ aptamer is smaller than known analogs. The proposed aptamer is highly selective for the RBD protein from the Wuhan-Hu-1 strain and does not form complexes with the RBD from Beta, Delta and Omicron strains. Experimental and theoretical studies together revealed the molecular mechanism of aptamer binding. The aptamer occupies the same binding site as ACE2 when bound to the RBD. The 3'-end of the MEZ aptamer is important for complex formation and is responsible for the discrimination of the RBD protein from a specific strain. The 5'-end is responsible for the formation of a loop in the 3D structure of the aptamer, which is important for proper binding.

Ancient and modern mechanisms compete in progesterone receptor activation

The progesterone receptor (PR) belongs to the steroid receptor family of ligand-regulated transcription factors, controlling genes important for development, metabolism, and reproduction. Understanding how diverse ligands bind and modulate PR activity will illuminate the design of ligands that control PR-driven signaling pathways. Here, we use molecular dynamics simulations to investigate how PR dynamics are altered by functionally diverse ligands. Using a library of 33 steroidal ligands that range from inactive to EC50 < 0.1 nM, we reveal an unexpected evolutionary basis for the wide gamut of activation. While other oxosteroid receptors employ an evolutionarily conserved mechanism dependent on a hydrogen bond between the receptor and ligand, extant PR has evolved a preference for activation that is not reliant on this polar interaction. We demonstrate that potent ligands utilize the modern PR mechanism while weaker ligands coopt the defunct ancestral mechanism by forming hydrogen bonds with Asn719. Based on their structures and dynamic signatures, ligands partition into four classes (inactive, weak, moderate and high potency) that interact distinctly with the PR binding pocket. Further, we use luciferase reporter assays and PR mutants to probe the roles of pocket residues in mediating distinct PR mechanisms. This combination of MD simulations and in vitro studies provide insight into how the evolutionary history of PR shapes its response to diverse ligands.

Probing allosteric communication with combined molecular dynamics simulations and network analysis

Understanding the allosteric mechanisms within biomolecules involved in diseases is of paramount importance for drug discovery. Indeed, characterizing communication pathways and critical hotspots in signal transduction can guide a rational approach to leverage allosteric modulation for therapeutic purposes. While the atomistic signatures of allosteric processes are difficult to determine experimentally, computational methods can be a remarkable resource. Network analysis built on Molecular Dynamics simulation data is particularly suited in this respect and is gradually becoming of routine use. Herein, we collect the recent literature in the field, discussing different aspects and available options for network construction and analysis. We further highlight interesting refinements and extensions, eventually providing our perspective on this topic.

Evolutionary rewiring of the dynamic network underpinning allosteric epistasis in NS1 of influenza A virus

Viral proteins frequently mutate to evade or antagonize host innate immune responses, yet the impact of these mutations on the molecular energy landscape remains unclear. Epistasis, the intramolecular communications between mutations, often renders the combined mutational effects unpredictable. Nonstructural protein 1 (NS1) is a major virulence factor of the influenza A virus (IAV) that activates host PI3K by binding to its p85β subunit. Here, we present the deep analysis for the impact of evolutionary mutations in NS1 that emerged between the 1918 pandemic IAV strain and its descendant PR8 strain. Our analysis reveal how the mutations rewired inter-residue communications which underlies long-range allosteric and epistatic networks in NS1. Our findings show that PR8 NS1 binds to p85β with approximately 10-fold greater affinity than 1918 NS1 due to allosteric mutational effects. Notably, these mutations also exhibited long-range epistatic effects. NMR chemical shift perturbation and methyl-axis order parameter analyses revealed that the mutations induced long-range structural and dynamic changes in PR8 NS1, enhancing its affinity to p85β. Complementary MD simulations and graph-based network analysis uncover how these mutations rewire dynamic residue interaction networks, which underlies the long-range epistasis and allosteric effects on p85β-binding affinity. Significantly, we find that conformational dynamics of residues with high betweenness centrality play a crucial role in communications between network communities and are highly conserved across influenza A virus evolution. These findings advance our mechanistic understanding of the allosteric and epistatic communications between distant residues and provides insight into their role in the molecular evolution of NS1.

Isolation, Virtual Screening, and Evaluation of Hazelnut-Derived Immunoactive Peptides for the Inhibition of SARS-CoV-2 Main Protease

The aim of this study is to validate the activity of hazelnut (Corylus avellana L.)-derived immunoactive peptides inhibiting the main protease (Mpro) of SARS-CoV-2 and further unveil their interaction mechanism using in vitro assays, molecular dynamics (MD) simulations, and binding free energy calculations. In general, the enzymatic hydrolysis components, especially molecular weight < 3 kDa, possess good immune activity as measured by the proliferation ability of mouse splenic lymphocytes and phagocytic activity of mouse peritoneal macrophages. Over 866 unique peptide sequences were isolated, purified, and then identified by nanohigh-performance liquid chromatography/tandem mass spectrometry (NANO-HPLC-MS/MS) from hazelnut protein hydrolysates, but Trp-Trp-Asn-Leu-Asn (WWNLN) and Trp-Ala-Val-Leu-Lys (WAVLK) in particular are found to increase the cell viability and phagocytic capacity of RAW264.7 macrophages as well as promote the secretion of the cytokines nitric oxide (NO), tumor necrosis factor-α (TNF-α), and interleukin-1β (IL-1β). Fluorescence resonance energy transfer assay elucidated that WWNLN and WAVLK exhibit excellent inhibitory potency against Mpro, with IC50 values of 6.695 and 16.750 μM, respectively. Classical all-atom MD simulations show that hydrogen bonds play a pivotal role in stabilizing the complex conformation and protein-peptide interaction. Molecular Mechanics/Generalized Born Surface Area (MM/GBSA) calculation indicates that WWNLN has a lower binding free energy with Mpro than WAVLK. Furthermore, adsorption, distribution, metabolism, excretion, and toxicity (ADMET) predictions illustrate favorable drug-likeness and pharmacokinetic properties of WWNLN compared to WAVLK. This study provides a new understanding of the immunomodulatory activity of hazelnut hydrolysates and sheds light on peptide inhibitors targeting Mpro.

Prediction of Conformational Ensembles and Structural Effects of State-Switching Allosteric Mutants in the Protein Kinases Using Comparative Analysis of AlphaFold2 Adaptations with Sequence Masking and Shallow Subsampling

Despite the success of AlphaFold2 approaches in predicting single protein structures, these methods showed intrinsic limitations in predicting multiple functional conformations of allosteric proteins and have been challenged to accurately capture of the effects of single point mutations that induced significant structural changes. We systematically examined several implementations of AlphaFold2 methods to predict conformational ensembles for state-switching mutants of the ABL kinase. The results revealed that a combination of randomized alanine sequence masking with shallow multiple sequence alignment subsampling can significantly expand the conformational diversity of the predicted structural ensembles and capture shifts in populations of the active and inactive ABL states. Consistent with the NMR experiments, the predicted conformational ensembles for M309L/L320I and M309L/H415P ABL mutants that perturb the regulatory spine networks featured the increased population of the fully closed inactive state. On the other hand, the predicted conformational ensembles for the G269E/M309L/T334I and M309L/L320I/T334I triple ABL mutants that share activating T334I gate-keeper substitution are dominated by the active ABL form. The proposed adaptation of AlphaFold can reproduce the experimentally observed mutation-induced redistributions in the relative populations of the active and inactive ABL states and capture the effects of regulatory mutations on allosteric structural rearrangements of the kinase domain. The ensemble-based network analysis complemented AlphaFold predictions by revealing allosteric mediating centers that often directly correspond to state-switching mutational sites or reside in their immediate local structural proximity, which may explain the global effect of regulatory mutations on structural changes between the ABL states. This study suggested that attention-based learning of long-range dependencies between sequence positions in homologous folds and deciphering patterns of allosteric interactions may further augment the predictive abilities of AlphaFold methods for modeling of alternative protein sates, conformational ensembles and mutation-induced structural transformations.

AlphaFold2 Predictions of Conformational Ensembles and Atomistic Simulations of the SARS-CoV-2 Spike XBB Lineages Reveal Epistatic Couplings between Convergent Mutational Hotspots that Control ACE2 Affinity

In this study, we combined AlphaFold-based atomistic structural modeling, microsecond molecular simulations, mutational profiling, and network analysis to characterize binding mechanisms of the SARS-CoV-2 spike protein with the host receptor ACE2 for a series of Omicron XBB variants including XBB.1.5, XBB.1.5+L455F, XBB.1.5+F456L, and XBB.1.5+L455F+F456L. AlphaFold-based structural and dynamic modeling of SARS-CoV-2 Spike XBB lineages can accurately predict the experimental structures and characterize conformational ensembles of the spike protein complexes with the ACE2. Microsecond molecular dynamics simulations identified important differences in the conformational landscapes and equilibrium ensembles of the XBB variants, suggesting that combining AlphaFold predictions of multiple conformations with molecular dynamics simulations can provide a complementary approach for the characterization of functional protein states and binding mechanisms. Using the ensemble-based mutational profiling of protein residues and physics-based rigorous calculations of binding affinities, we identified binding energy hotspots and characterized the molecular basis underlying epistatic couplings between convergent mutational hotspots. Consistent with the experiments, the results revealed the mediating role of the Q493 hotspot in the synchronization of epistatic couplings between L455F and F456L mutations, providing a quantitative insight into the energetic determinants underlying binding differences between XBB lineages. We also proposed a network-based perturbation approach for mutational profiling of allosteric communications and uncovered the important relationships between allosteric centers mediating long-range communication and binding hotspots of epistatic couplings. The results of this study support a mechanism in which the binding mechanisms of the XBB variants may be determined by epistatic effects between convergent evolutionary hotspots that control ACE2 binding.

Secondary Conformational Checkpoint in CRISPR-Cas9

A specific checkpoint between target DNA binding and cleavage primarily governs the precision of Cas9 gene editing. Although various CRISPR-Cas9 variants have been developed to improve DNA cleavage accuracy, we still lack a comprehensive understanding of how they work at the molecular level. Herein, we have focused on studying the late-stage conformational transitions of Cas9 and an evolved Cas9 mutant (evoCas9) that start from the precleavage state. Our submilliseconds of dynamic simulations reveal that the presence of base mismatches leads the HNH nuclease domain of Cas9 to alter its principal functional modes of motion, thereby impairing its conformational activation. This observation suggests the existence of a secondary conformational checkpoint that fine-tunes the final DNA cleavage activation. Remarkably, evoCas9 is prone to deviating from the normal activation pathway with base mismatches. This is characterized by a noticeable shift in the positioning of the HNH domain and a significantly perturbed allosteric communication network within the enzyme. Therefore, the mutations evolved in evoCas9 also reinforce the secondary checkpoint in addition to the previously identified primary checkpoint, collectively ensuring this variant's high gene-editing accuracy. This mechanism should also apply to other Cas9-guide RNA variants with enhanced fidelity.

A combined in vitro and in silico study of the inhibitory mechanism of angiotensin-converting enzyme with peanut peptides

Food-derived peptides with low molecular weight, high bioavailability, and good absorptivity have been exploited as angiotensin-converting enzyme (ACE) inhibitors. In the present study, in-vitro inhibition kinetics of peanut peptides, in silico screening, validation of ACE inhibitory activity, molecular dynamics (MD) simulations, and HUVEC cells were performed to systematically identify the inhibitory mechanism of ACE interacting with peanut peptides. The results indicate that FPHPP, FPHY, and FPHFD peptides have good thermal, pH, and digestive stability. MD trajectories elucidate the dynamic correlation between peptides and ACE and verify the specific binding interaction. Noteworthily, FPHPP is the best inhibitor with a strongest binding affinity and significantly increases NO, SOD production, and AT2R expression, and decreases ROS, MDA, ET-1 levels, ACE, and AT1R accumulation in Ang II-injury HUVEC cells.

Cholesterol Dependence of the Conformational Changes in Metabotropic Glutamate Receptor 1

Metabotropic glutamate receptors (mGluRs) are class C G protein-coupled receptors that function as obligate dimers in regulating neurotransmission and synaptic plasticity in the central nervous system. The mGluR1 subtype has been shown to be modulated by the membrane lipid environment, particularly cholesterol, though the molecular mechanisms remain elusive. In this study, we employed all-atom molecular dynamics simulations to investigate the effects of cholesterol on the conformational dynamics of the mGluR1 seven-transmembrane (7TM) domain in an inactive state model. Simulations were performed with three different cholesterol concentrations (0%, 10%, and 25%) in a palmitoyl-oleoyl phosphatidylcholine (POPC) lipid bilayer system. Our results demonstrate that cholesterol induces conformational changes in the mGluR1 dimer more significantly than in the individual protomers. Notably, cholesterol modulates the dynamics and conformations of the TM1 and TM2 helices at the dimer interface. Interestingly, an intermediate cholesterol concentration of 10% elicits more pronounced conformational changes compared to both cholesterol-depleted (0%) and cholesterol-enriched (25%) systems. Specific electrostatic interaction unique to the 10% cholesterol system further corroborate these conformational differences. Given the high sequence conservation of the 7TM domains across mGluR subtypes, the cholesterol-dependent effects observed in mGluR1 are likely applicable to other members of this receptor family. Our findings provide atomistic insights into how cholesterol modulates the conformational landscape of mGluRs, which could impact their function and signaling mechanisms.

The role of the correlated motion(s) of the chromophore in photoswitching of green and red forms of the photoconvertible fluorescent protein mSAASoti

Wild-type SAASoti and its monomeric variant mSAASoti can undergo phototransformations, including reversible photoswitching of the green form to a nonfluorescent state and irreversible green-to-red photoconversion. In this study, we extend the photochemistry of mSAASoti variants to enable reversible photoswitching of the red form. This result is achieved by rational and site-saturated mutagenesis of the M163 and F177 residues. In the case of mSAASoti it is M163T substitution that leads to the fastest switching and the most photostable variant, and reversible photoswitching can be observed for both green and red forms when expressed in eukaryotic cells. We obtained a 13-fold increase in the switching efficiency with the maximum switching contrast of the green form and the appearance of comparable switching of the red form for the C21N/M163T mSAASoti variant. The crystal structure of the C21N mSAASoti in its green on-state was obtained for the first time at 3.0 Å resolution, and it is in good agreement with previously calculated 3D-model. Dynamic network analysis reveals that efficient photoswitching occurs if motions of the 66H residue and phenyl fragment of chromophore are correlated and these moieties belong to the same community.

Ensemble-Based Mutational Profiling and Network Analysis of the SARS-CoV-2 Spike Omicron XBB Lineages for Interactions with the ACE2 Receptor and Antibodies: Cooperation of Binding Hotspots in Mediating Epistatic Couplings Underlies Binding Mechanism and Immune Escape

In this study, we performed a computational study of binding mechanisms for the SARS-CoV-2 spike Omicron XBB lineages with the host cell receptor ACE2 and a panel of diverse class one antibodies. The central objective of this investigation was to examine the molecular factors underlying epistatic couplings among convergent evolution hotspots that enable optimal balancing of ACE2 binding and antibody evasion for Omicron variants BA.1, BA2, BA.3, BA.4/BA.5, BQ.1.1, XBB.1, XBB.1.5, and XBB.1.5 + L455F/F456L. By combining evolutionary analysis, molecular dynamics simulations, and ensemble-based mutational scanning of spike protein residues in complexes with ACE2, we identified structural stability and binding affinity hotspots that are consistent with the results of biochemical studies. In agreement with the results of deep mutational scanning experiments, our quantitative analysis correctly reproduced strong and variant-specific epistatic effects in the XBB.1.5 and BA.2 variants. It was shown that Y453W and F456L mutations can enhance ACE2 binding when coupled with Q493 in XBB.1.5, while these mutations become destabilized when coupled with the R493 position in the BA.2 variant. The results provided a molecular rationale of the epistatic mechanism in Omicron variants, showing a central role of the Q493/R493 hotspot in modulating epistatic couplings between convergent mutational sites L455F and F456L in XBB lineages. The results of mutational scanning and binding analysis of the Omicron XBB spike variants with ACE2 receptors and a panel of class one antibodies provide a quantitative rationale for the experimental evidence that epistatic interactions of the physically proximal binding hotspots Y501, R498, Q493, L455F, and F456L can determine strong ACE2 binding, while convergent mutational sites F456L and F486P are instrumental in mediating broad antibody resistance. The study supports a mechanism in which the impact on ACE2 binding affinity is mediated through a small group of universal binding hotspots, while the effect of immune evasion could be more variant-dependent and modulated by convergent mutational sites in the conformationally adaptable spike regions.

Predicting permeation of compounds across the outer membrane of P. aeruginosa using molecular descriptors

The ability Gram-negative pathogens have at adapting and protecting themselves against antibiotics has increasingly become a public health threat. Data-driven models identifying molecular properties that correlate with outer membrane (OM) permeation and growth inhibition while avoiding efflux could guide the discovery of novel classes of antibiotics. Here we evaluate 174 molecular descriptors in 1260 antimicrobial compounds and study their correlations with antibacterial activity in Gram-negative Pseudomonas aeruginosa. The descriptors are derived from traditional approaches quantifying the compounds' intrinsic physicochemical properties, together with, bacterium-specific from ensemble docking of compounds targeting specific MexB binding pockets, and all-atom molecular dynamics simulations in different subregions of the OM model. Using these descriptors and the measured inhibitory concentrations, we design a statistical protocol to identify predictors of OM permeation/inhibition. We find consistent rules across most of our data highlighting the role of the interaction between the compounds and the OM. An implementation of the rules uncovered in our study is shown, and it demonstrates the accuracy of our approach in a set of previously unseen compounds. Our analysis sheds new light on the key properties drug candidates need to effectively permeate/inhibit P. aeruginosa, and opens the gate to similar data-driven studies in other Gram-negative pathogens.

Tracing Allostery in the Spliceosome Ski2-like RNA Helicase Brr2

RNA ATPases/helicases remodel substrate RNA-protein complexes in distinct ways. The different RNA ATPases/helicases, taking part in the spliceosome complex, reshape the RNA/RNA-protein contacts to enable premature-mRNA splicing. Among them, the bad response to refrigeration 2 (Brr2) helicase promotes U4/U6 small nuclear (sn)RNA unwinding via ATP-driven translocation of the U4 snRNA strand, thus playing a pivotal role during the activation, catalytic, and disassembly phases of splicing. The plastic Brr2 architecture consists of an enzymatically active N-terminal cassette (N-cassette) and a structurally similar but inactive C-terminal cassette (C-cassette). The C-cassette, along with other allosteric effectors and regulators, tightly and timely controls Brr2's function via an elusive mechanism. Here, microsecond-long molecular dynamics simulations, dynamical network theory, and community network analysis are combined to elucidate how allosteric effectors/regulators modulate the Brr2 function. We unexpectedly reveal that U4 snRNA itself acts as an allosteric regulator, amplifying the cross-talk of distal Brr2 domains and triggering a conformational reorganization of the protein. Our findings offer fundamental understanding into Brr2's mechanism of action and broaden our knowledge on the sophisticated regulatory mechanisms by which spliceosome ATPases/helicases control gene expression. This includes their allosteric regulation exerted by client RNA strands, a mechanism that may be broadly applicable to other RNA-dependent ATPases/helicases.

An allosteric mechanism for potent inhibition of SARS-CoV-2 main proteinase

The main proteinase (Mpro) of SARS-CoV-2 plays a critical role in cleaving viral polyproteins into functional proteins required for viral replication and assembly, making it a prime drug target for COVID-19. It is well known that noncompetitive inhibition offers potential therapeutic options for treating COVID-19, which can effectively reduce the likelihood of cross-reactivity with other proteins and increase the selectivity of the drug. Therefore, the discovery of allosteric sites of Mpro has both scientific and practical significance. In this study, we explored the binding characteristics and inhibiting process of Mpro activity by two recently reported allosteric inhibitors, pelitinib and AT7519 which were obtained by the X-ray screening experiments, to probe the allosteric mechanism via molecular dynamic (MD) simulations. We found that pelitinib and AT7519 can stably bind to Mpro far from the active site. The binding affinity is estimated to be -24.37 ± 4.14 and - 26.96 ± 4.05 kcal/mol for pelitinib and AT7519, respectively, which is considerably stable compared with orthosteric drugs. Furthermore, the strong binding caused clear changes in the catalytic site of Mpro, thus decreasing the substrate accessibility. The community network analysis also validated that pelitinib and AT7519 strengthened intra- and inter-domain communication of Mpro dimer, resulting in a rigid Mpro, which could negatively impact substrate binding. In summary, our findings provide the detailed working mechanism for the two experimentally observed allosteric sites of Mpro. These allosteric sites greatly enhance the 'druggability' of Mpro and represent attractive targets for the development of new Mpro inhibitors.

Synergistic inhibition mechanism of quinazolinone and piperacillin on penicillin-binding protein 2a: a promising approach for combating methicillin-resistant Staphylococcus aureus

The production of penicillin-binding protein 2a (PBP2a), a cell wall synthesis protein, is primarily responsible for the high-level resistance observed in methicillin-resistant Staphylococcus aureus (MRSA). PBP2a exhibits a significantly reduced affinity for most β-lactam antibiotics owing to its tightly closed active site. Quinazolinones (QNE), a novel class of non-β-lactam antibiotics, could initiate the allosteric regulation of PBP2a, resulting in the opening of the initially closed active pocket. Based on our previous study, we have a basic understanding of the dual-site inhibitor ceftaroline (CFT) induced allosteric regulation of PBP2a. However, there are still limitations in the knowledge of how combining medicines, QNE and piperacillin (PIP), induce the allosteric response of PBP2a and inhibit its function. Herein, molecular dynamics (MD) simulations were performed to elucidate the intricate mechanisms underlying the combination mode of QNE and PIP. Our study successfully captured the opening process of the active pocket upon the binding of the QNE at the allosteric site, which alters the signaling pathways with a favorable transmission to the active site. Subsequent docking experiments with different conformational states of the active pocket indicated that all three inhibitors, PIP, QNE, and CFT, exhibited higher docking scores and more favorable docking poses to the open active pocket. These findings reveal the implied mechanism of QNE-mediated allostery underlying combination therapy and provide novel insights into developing innovative therapeutic modalities against MRSA.Communicated by Ramaswamy H. Sarma.

High-fidelity, hyper-accurate, and evolved mutants rewire atomic-level communication in CRISPR-Cas9

The high-fidelity (HF1), hyper-accurate (Hypa), and evolved (Evo) variants of the CRISPR-associated protein 9 (Cas9) endonuclease are critical tools to mitigate off-target effects in the application of CRISPR-Cas9 technology. The mechanisms by which mutations in recognition subdomain 3 (Rec3) mediate specificity in these variants are poorly understood. Here, solution nuclear magnetic resonance and molecular dynamics simulations establish the structural and dynamic effects of high-specificity mutations in Rec3, and how they propagate the allosteric signal of Cas9. We reveal conserved structural changes and dynamic differences at regions of Rec3 that interface with the RNA:DNA hybrid, transducing chemical signals from Rec3 to the catalytic His-Asn-His (HNH) domain. The variants remodel the communication sourcing from the Rec3 α helix 37, previously shown to sense target DNA complementarity, either directly or allosterically. This mechanism increases communication between the DNA mismatch recognition helix and the HNH active site, shedding light on the structure and dynamics underlying Cas9 specificity and providing insight for future engineering principles.

The energy landscape of the ribosome

The ribosome is a prototypical assembly that can be used to establish general principles and techniques for the study of biological molecular machines. Motivated by the fact that the dynamics of every biomolecule is governed by an underlying energy landscape, there has been great interest to understand and quantify ribosome energetics. In the present review, we will focus on theoretical and computational strategies for probing the interactions that shape the energy landscape of the ribosome, with an emphasis on more recent studies of the elongation cycle. These efforts include the application of quantum mechanical methods for describing chemical kinetics, as well as classical descriptions to characterize slower (microsecond to millisecond) large-scale (10-100 Å) rearrangements, where motion is described in terms of diffusion across an energy landscape. Together, these studies provide broad insights into the factors that control a diverse range of dynamical processes in this assembly.

Allostery in Protein Tyrosine Phosphatases is Enabled by Divergent Dynamics

Dynamics-driven allostery provides important insights into the working mechanics of proteins, especially enzymes. In this study, we employ this paradigm to answer a basic question: in enzyme superfamilies, where the catalytic mechanism, active sites, and protein fold are conserved, what accounts for the difference in the catalytic prowess of the individual members? We show that when subtle changes in sequence do not translate to changes in structure, they do translate to changes in dynamics. We use sequentially diverse PTP1B, TbPTP1, and YopH as representatives of the conserved protein tyrosine phosphatase (PTP) superfamily. Using amino acid network analysis of group behavior (community analysis) and influential node dominance on networks (eigenvector centrality), we explain the dynamic basis of the catalytic variations seen between the three proteins. Importantly, we explain how a dynamics-based blueprint makes PTP1B amenable to allosteric control and how the same is abstracted in TbPTP1 and YopH.

Epistasis arises from shifting the rate-limiting step during enzyme evolution of a β-lactamase

Epistasis, the non-additive effect of mutations, can provide combinatorial improvements to enzyme activity that substantially exceed the gains from individual mutations. Yet the molecular mechanisms of epistasis remain elusive, undermining our ability to predict pathogen evolution and engineer biocatalysts. Here we reveal how directed evolution of a β-lactamase yielded highly epistatic activity enhancements. Evolution selected four mutations that increase antibiotic resistance 40-fold, despite their marginal individual effects (≤2-fold). Synergistic improvements coincided with the introduction of super-stochiometric burst kinetics, indicating that epistasis is rooted in the enzyme's conformational dynamics. Our analysis reveals that epistasis stemmed from distinct effects of each mutation on the catalytic cycle. The initial mutation increased protein flexibility and accelerated substrate binding, which is rate-limiting in the wild-type enzyme. Subsequent mutations predominantly boosted the chemical steps by fine-tuning substrate interactions. Our work identifies an overlooked cause for epistasis: changing the rate-limiting step can result in substantial synergy that boosts enzyme activity.

Perspectives on Computational Enzyme Modeling: From Mechanisms to Design and Drug Development

Understanding enzyme mechanisms is essential for unraveling the complex molecular machinery of life. In this review, we survey the field of computational enzymology, highlighting key principles governing enzyme mechanisms and discussing ongoing challenges and promising advances. Over the years, computer simulations have become indispensable in the study of enzyme mechanisms, with the integration of experimental and computational exploration now established as a holistic approach to gain deep insights into enzymatic catalysis. Numerous studies have demonstrated the power of computer simulations in characterizing reaction pathways, transition states, substrate selectivity, product distribution, and dynamic conformational changes for various enzymes. Nevertheless, significant challenges remain in investigating the mechanisms of complex multistep reactions, large-scale conformational changes, and allosteric regulation. Beyond mechanistic studies, computational enzyme modeling has emerged as an essential tool for computer-aided enzyme design and the rational discovery of covalent drugs for targeted therapies. Overall, enzyme design/engineering and covalent drug development can greatly benefit from our understanding of the detailed mechanisms of enzymes, such as protein dynamics, entropy contributions, and allostery, as revealed by computational studies. Such a convergence of different research approaches is expected to continue, creating synergies in enzyme research. This review, by outlining the ever-expanding field of enzyme research, aims to provide guidance for future research directions and facilitate new developments in this important and evolving field.

Identification of Residues Potentially Involved in Optical Shifts in the Water-Soluble Chlorophyll a-Binding Protein through Molecular Dynamics Simulations

Reversible light and thermally induced spectral shifts are universally observed in a wide variety of pigment-protein complexes at temperatures ranging from cryogenic to ambient. In this paper, we employed large-scale molecular dynamics (MD) simulations of a prototypical pigment-protein complex to better understand these shifts at a molecular scale. Although multiple mechanisms have been proposed over the years, no verification of these proposals via MD simulations has thus far been performed; our work represents the first step in this direction. From simulations of the water-soluble chlorophyll-binding protein complex, we determined that rearrangements of long hydrogen bonds were unlikely to be the origin of the multiwell landscape features necessary to explain observed spectral shifts. We also assessed small motions of amino acid residues and identified side chain rotations of some of these residues as likely candidates for the origin of relevant multiwell landscape features. The protein free-energy landscapes associated with side chain rotations feature energy barriers of around 1100-1600 cm-1, in agreement with optical spectroscopy results, with the most promising residue type associated with experimental signatures being serine, which possesses a symmetric triple-well landscape and moment of inertia of a relevant magnitude.

Ultrafast vibrational energy redistribution in cyclotrimethylene trinitramine (RDX)

The microscopic mechanism of the energy transfer in cyclotrimethylene trinitramine (RDX) is of particular importance for the study of the energy release process in high-energy materials. In this work, an effective vibrational Hamiltonian based on normal modes (NMs) has been introduced to study the energy transfer process of RDX. The results suggest that the energy redistribution in RDX can be characterized as an ultrafast process with a time scale of 25 fs, during which the energy can be rapidly localized to the -NNO2 twisting mode (vNNO2), the N-N stretching mode (vN-N), and the C-H stretching mode (vC-H). Here, the vNNO2 and vN-N modes are directly related to the cleavage and dissociation of the N-N bond in RDX and, therefore, can be referred to as "active modes." More importantly, we found that the energy can be rapidly transferred from the vC-H mode to the vNNO2 mode due to their strong coupling. From this perspective, the vC-H mode can be regarded as an "energy collector" that plays a pivotal role in supplying energy to the "active modes." In addition, the bond order analysis shows that the dissociation of the N-N bonds of RDX follows a combined twisting and stretching path along the N-N bond. This could be an illustration of the further exothermic decomposition triggered by the accumulation of vibrational energy. The present study reveals the microscopic mechanism for the vibrational energy redistribution process of RDX, which is important for further investigation of the energy transfer process in high-energy materials.

Single-molecule FRET probes allosteric effects on protein-translocating pore loops of a AAA+ machine

AAA+ proteins (ATPases associated with various cellular activities) comprise a family of powerful ring-shaped ATP-dependent translocases that carry out numerous vital substrate-remodeling functions. ClpB is a AAA+ protein disaggregation machine that forms a two-tiered hexameric ring, with flexible pore loops protruding into its center and binding to substrate proteins. It remains unknown whether these pore loops contribute only passively to substrate-protein threading or have a more active role. Recently, we have applied single-molecule FRET spectroscopy to directly measure the dynamics of substrate-binding pore loops in ClpB. We have reported that the three pore loops of ClpB (PL1-3) undergo large-scale fluctuations on the microsecond timescale that are likely to be mechanistically important for disaggregation. Here, using single-molecule FRET, we study the allosteric coupling between the pore loops and the two nucleotide-binding domains of ClpB (NBD1-2). By mutating the conserved Walker B motifs within the NBDs to abolish ATP hydrolysis, we demonstrate how the nucleotide state of each NBD tunes pore-loop dynamics. This effect is surprisingly long-ranged; in particular, PL2 and PL3 respond differentially to a Walker B mutation in either NBD1 or NBD2, as well as to mutations in both. We characterize the conformational dynamics of pore loops and the allosteric paths connecting NBDs to pore loops by molecular dynamics simulations and find that both principal motions and allosteric paths can be altered by changing the ATPase state of ClpB. Remarkably, PL3, which is highly conserved in AAA+ machines, is found to favor an upward conformation when only NBD1 undergoes ATP hydrolysis but a downward conformation when NBD2 is active. These results explicitly demonstrate a significant long-range allosteric effect of ATP hydrolysis sites on pore-loop dynamics. Pore loops are therefore established as active participants that undergo ATP-dependent conformational changes to translocate substrate proteins through the central pores of AAA+ machines.

Decoupling the dynamic mechanism revealed by FGFR2 mutation-induced population shift

The fibroblast growth factor receptor 2 (FGFR2) is a key component in cellular signaling networks, and its dysfunctional activation has been implicated in various diseases including cancer and developmental disorders. Mutations at the activation loop (A-loop) have been suggested to trigger an increased basal kinase activity. However, the molecular mechanism underlying this highly dynamic process has not been fully understood due to the limitation of static structural information. Here, we conducted multiple, large-scale Gaussian accelerated molecular dynamics simulations of five (K659E, K659N, K659M, K659Q, and K659T) FGFR2 mutants at the A-loop, and comprehensively analyzed the dynamic molecular basis of FGFR2 activation. The results quantified the population shift of each system, revealing that all mutants had a higher proportion of active-like states. Using Markov state models, we extracted the representative structure of different conformational states and identified key residues related to the increased kinase activity. Furthermore, community network analysis showed enhanced information connections in the mutants, highlighting the long-range allosteric communication between the A-loop and the hinge region. Our findings may provide insights into the dynamic mechanism for FGFR2 dysfunctional activation and allosteric drug discovery.Communicated by Ramaswamy H. Sarma.

Molecular mechanism of rhinovirus escape from the Pyrazolo[3,4-d]pyrimidine capsid-binding inhibitor OBR-5-340 via mutations distant from the binding pocket: Derivatives that brake resistance

Rhinoviruses (RVs) cause the common cold. Attempts at discovering small molecule inhibitors have mainly concentrated on compounds supplanting the medium chain fatty acids residing in the sixty icosahedral symmetry-related hydrophobic pockets of the viral capsid of the Rhinovirus-A and -B species. High-affinity binding to these pockets stabilizes the capsid against structural changes necessary for the release of the ss(+) RNA genome into the cytosol of the host cell. However, single-point mutations may abolish this binding. RV-B5 is one of several RVs that are naturally resistant against the well-established antiviral agent pleconaril. However, RV-B5 is strongly inhibited by the pyrazolopyrimidine OBR-5-340. Here, we report on isolation and characterization of RV-B5 mutants escaping OBR-5-340 inhibition and show that substitution of amino acid residues not only within the binding pocket but also remote from the binding pocket hamper inhibition. Molecular dynamics network analysis revealed that strong inhibition occurs when an ensemble of several sequence stretches of the capsid proteins enveloping OBR-5-340 move together with OBR-5-340. Mutations abrogating this dynamic, regardless of whether being localized within the binding pocket or distant from it result in escape from inhibition. Pyrazolo [3,4-d]pyrimidine derivatives overcoming OBR-5-340 escape of various RV-B5 mutants were identified. Our work contributes to the understanding of the properties of capsid-binding inhibitors necessary for potent and broad-spectrum inhibition of RVs.

Interactive computational and experimental approaches improve the sensitivity of periplasmic binding protein-based nicotine biosensors for measurements in biofluids

We developed fluorescent protein sensors for nicotine with improved sensitivity. For iNicSnFR12 at pH 7.4, the proportionality constant for ∆F/F0vs [nicotine] (δ-slope, 2.7 μM-1) is 6.1-fold higher than the previously reported iNicSnFR3a. The activated state of iNicSnFR12 has a fluorescence quantum yield of at least 0.6. We measured similar dose-response relations for the nicotine-induced absorbance increase and fluorescence increase, suggesting that the absorbance increase leads to the fluorescence increase via the previously described nicotine-induced conformational change, the 'candle snuffer' mechanism. Molecular dynamics (MD) simulations identified a binding pose for nicotine, previously indeterminate from experimental data. MD simulations also showed that Helix 4 of the periplasmic binding protein (PBP) domain appears tilted in iNicSnFR12 relative to iNicSnFR3a, likely altering allosteric network(s) that link the ligand binding site to the fluorophore. In thermal melt experiments, nicotine stabilized the PBP of the tested iNicSnFR variants. iNicSnFR12 resolved nicotine in diluted mouse and human serum at 100 nM, the peak [nicotine] that occurs during smoking or vaping, and possibly at the decreasing levels during intervals between sessions. NicSnFR12 was also partially activated by unidentified endogenous ligand(s) in biofluids. Improved iNicSnFR12 variants could become the molecular sensors in continuous nicotine monitors for animal and human biofluids.

The shortest path method (SPM) webserver for computational enzyme design

SPMweb is the online webserver of the Shortest Path Map (SPM) tool for identifying the key conformationally-relevant positions of a given enzyme structure and dynamics. The server is built on top of the DynaComm.py code and enables the calculation and visualization of the SPM pathways. SPMweb is easy-to-use as it only requires three input files: the three-dimensional structure of the protein of interest, and the two matrices (distance and correlation) previously computed from a Molecular Dynamics simulation. We provide in this publication information on how to generate the files for SPM construction even for non-expert users and discuss the most relevant parameters that can be modified. The tool is extremely fast (it takes less than one minute per job), thus allowing the rapid identification of distal positions connected to the active site pocket of the enzyme. SPM applications expand from computational enzyme design, especially if combined with other tools to identify the preferred substitution at the identified position, but also to rationalizing allosteric regulation, and even cryptic pocket identification for drug discovery. The simple user interface and setup make the SPM tool accessible to the whole scientific community. SPMweb is freely available for academia at http://spmosuna.com/.

New design strategies for ultra-specific CRISPR-Cas13a-based RNA detection with single-nucleotide mismatch sensitivity

An increasingly pressing need for clinical diagnostics has required the development of novel nucleic acid-based detection technologies that are sensitive, fast, and inexpensive, and that can be deployed at point-of-care. Recently, the RNA-guided ribonuclease CRISPR-Cas13 has been successfully harnessed for such purposes. However, developing assays for detection of genetic variability, for example single-nucleotide polymorphisms, is still challenging and previously described design strategies are not always generalizable. Here, we expanded our characterization of LbuCas13a RNA-detection specificity by performing a combination of experimental RNA mismatch tolerance profiling, molecular dynamics simulations, protein, and crRNA engineering. We found certain positions in the crRNA-target-RNA duplex that are particularly sensitive to mismatches and establish the effect of RNA concentration in mismatch tolerance. Additionally, we determined that shortening the crRNA spacer or modifying the direct repeat of the crRNA leads to stricter specificities. Furthermore, we harnessed our understanding of LbuCas13a allosteric activation pathways through molecular dynamics and structure-guided engineering to develop novel Cas13a variants that display increased sensitivities to single-nucleotide mismatches. We deployed these Cas13a variants and crRNA design strategies to achieve superior discrimination of SARS-CoV-2 strains compared to wild-type LbuCas13a. Together, our work provides new design criteria and Cas13a variants to use in future easier-to-implement Cas13-based RNA detection applications.

Unveiling the RNA-mediated allosteric activation discloses functional hotspots in CRISPR-Cas13a

Cas13a is a recent addition to the CRISPR-Cas toolkit that exclusively targets RNA, which makes it a promising tool for RNA detection. It utilizes a CRISPR RNA (crRNA) to target RNA sequences and trigger a composite active site formed by two 'Higher Eukaryotes and Prokaryotes Nucleotide' (HEPN) domains, cleaving any solvent-exposed RNA. In this system, an intriguing form of allosteric communication controls the RNA cleavage activity, yet its molecular details are unknown. Here, multiple-microsecond molecular dynamics simulations are combined with graph theory to decipher this intricate activation mechanism. We show that the binding of a target RNA acts as an allosteric effector, by amplifying the communication signals over the dynamical noise through interactions of the crRNA at the buried HEPN1-2 interface. By introducing a novel Signal-to-Noise Ratio (SNR) of communication efficiency, we reveal critical allosteric residues-R377, N378, and R973-that rearrange their interactions upon target RNA binding. Alanine mutation of these residues is shown to select target RNA over an extended complementary sequence beyond guide-target duplex for RNA cleavage, establishing the functional significance of these hotspots. Collectively our findings offer a fundamental understanding of the Cas13a mechanism of action and pave new avenues for the development of highly selective RNA-based cleavage and detection tools.

Biased Signaling in Mutated Variants of β2-Adrenergic Receptor: Insights from Molecular Dynamics Simulations

The molecular basis of receptor bias in G protein-coupled receptors (GPCRs) caused by mutations that preferentially activate specific intracellular transducers over others remains poorly understood. Two experimentally identified biased variants of β2-adrenergic receptors (β2AR), a prototypical GPCR, are a triple mutant (T68F, Y132A, and Y219A) and a single mutant (Y219A); the former bias the receptor toward the β-arrestin pathway by disfavoring G protein engagement, while the latter induces G protein signaling explicitly due to selection against GPCR kinases (GRKs) that phosphorylate the receptor as a prerequisite of β-arrestin binding. Though rigorous characterizations have revealed functional implications of these mutations, the atomistic origin of the observed transducer selectivity is not clear. In this study, we investigated the allosteric mechanism of receptor bias in β2AR using microseconds of all-atom Gaussian accelerated molecular dynamics (GaMD) simulations. Our observations reveal distinct rearrangements in transmembrane helices, intracellular loop 3, and critical residues R1313.50 and Y3267.53 in the conserved motifs D(E)RY and NPxxY for the mutant receptors, leading to their specific transducer interactions. Moreover, partial dissociation of G protein from the receptor core is observed in the simulations of the triple mutant in contrast to the single mutant and wild-type receptor. The reorganization of allosteric communications from the extracellular agonist BI-167107 to the intracellular receptor-transducer interfaces drives the conformational rearrangements responsible for receptor bias in the single and triple mutants. The molecular insights into receptor bias of β2AR presented here could improve the understanding of biased signaling in GPCRs, potentially opening new avenues for designing novel therapeutics with fewer side-effects and superior efficacy.

Interactive computational and experimental approaches improve the sensitivity of periplasmic binding protein-based nicotine biosensors for measurements in biofluids

We developed fluorescent protein sensors for nicotine with improved sensitivity. For iNicSnFR12 at pH 7.4, the proportionality constant for Δ F / F 0 vs [nicotine] (δ-slope, 2.7 μM-1) is 6.1-fold higher than the previously reported iNicSnFR3a. The activated state of iNicSnFR12 has a fluorescence quantum yield of at least 0.6. We measured similar dose-response relations for the nicotine-induced absorbance increase and fluorescence increase, suggesting that the absorbance increase leads to the fluorescence increase via the previously described nicotine-induced conformational change, the "candle snuffer" mechanism. Molecular dynamics (MD) simulations identified a binding pose for nicotine, previously indeterminate from experimental data. MD simulations also showed that Helix 4 of the periplasmic binding protein (PBP) domain appears tilted in iNicSnFR12 relative to iNicSnFR3a, likely altering allosteric network(s) that link the ligand binding site to the fluorophore. In thermal melt experiments, nicotine stabilized the PBP of the tested iNicSnFR variants. iNicSnFR12 resolved nicotine in diluted mouse and human serum at 100 nM, the peak [nicotine] that occurs during smoking or vaping, and possibly at the decreasing levels during intervals between sessions. NicSnFR12 was also partially activated by unidentified endogenous ligand(s) in biofluids. Improved iNicSnFR12 variants could become the molecular sensors in continuous nicotine monitors for animal and human biofluids.

The Pivotal Distinction between Antagonists' and Agonists' Binding into Dopamine D4 Receptor-MD and FMO/PIEDA Studies

The dopamine D4 receptor (D4R) is a promising therapeutic target in widespread diseases, and the search for novel agonists and antagonists appears to be clinically relevant. The mechanism of binding to the receptor (R) for antagonists and agonists varies. In the present study, we conducted an in-depth computational study, teasing out key similarities and differences in binding modes, complex dynamics, and binding energies for D4R agonists and antagonists. The dynamic network method was applied to investigate the communication paths between the ligand (L) and G-protein binding site (GBS) of human D4R. Finally, the fragment molecular orbitals with pair interaction energy decomposition analysis (FMO/PIEDA) scheme was used to estimate the binding energies of L-R complexes. We found that a strong salt bridge with D3.32 initiates the inhibition of the dopamine D4 receptor. This interaction also occurs in the binding of agonists, but the change in the receptor conformation to the active state starts with interaction with cysteine C3.36. Such a mechanism may arise in the case of agonists unable to form a hydrogen bond with the serine S5.46, considered, so far, to be crucial in the activation of GPCRs. The energy calculations using the FMO/PIEDA method indicate that antagonists show higher residue occupancy of the receptor binding site than agonists, suggesting they could form relatively more stable complexes. Additionally, antagonists were characterized by repulsive interactions with S5.46 distinguishing them from agonists.

Thrombin - A Molecular Dynamics Perspective

Thrombin is a crucial enzyme involved in blood coagulation, essential for maintaining circulatory system integrity and preventing excessive bleeding. However, thrombin is also implicated in pathological conditions such as thrombosis and cancer. Despite the application of various experimental techniques, including X-ray crystallography, NMR spectroscopy, and HDXMS, none of these methods can precisely detect thrombin's dynamics and conformational ensembles at high spatial and temporal resolution. Fortunately, molecular dynamics (MD) simulation, a computational technique that allows the investigation of molecular functions and dynamics in atomic detail, can be used to explore thrombin behavior. This review summarizes recent MD simulation studies on thrombin and its interactions with other biomolecules. Specifically, the 17 studies discussed here provide insights into thrombin's switch between 'slow' and 'fast' forms, active and inactive forms, the role of Na+ binding, the effects of light chain mutation, and thrombin's interactions with other biomolecules. The findings of these studies have significant implications for developing new therapies for thrombosis and cancer. By understanding thrombin's complex behavior, researchers can design more effective drugs and treatments that target thrombin.

Unveiling local and global conformational changes and allosteric communications in SOD1 systems using molecular dynamics simulation and network analyses

BACKGROUND

Amyotrophic lateral sclerosis (ALS) is a serious neurodegenerative disorder affecting nerve cells in the brain and spinal cord that is caused by mutations in the superoxide dismutase 1 (SOD1) enzyme. ALS-related mutations cause misfolding, dimerisation instability, and increased formation of aggregates. The underlying allosteric mechanisms, however, remain obscure as far as details of their fundamental atomistic structure are concerned. Hence, this gap in knowledge limits the development of novel SOD1 inhibitors and the understanding of how disease-associated mutations in distal sites affect enzyme activity.

METHODS

We combined microsecond-scale based unbiased molecular dynamics (MD) simulation with network analysis to elucidate the local and global conformational changes and allosteric communications in SOD1 Apo (unmetallated form), Holo, Apo_CallA (mutant and unmetallated form), and Holo_CallA (mutant form) systems. To identify hotspot residues involved in SOD1 signalling and allosteric communications, we performed network centrality, community network, and path analyses.

RESULTS

Structural analyses showed that unmetallated SOD1 systems and cysteine mutations displayed large structural variations in the catalytic sites, affecting structural stability. Inter- and intra H-bond analyses identified several important residues crucial for maintaining interfacial stability, structural stability, and enzyme catalysis. Dynamic motion analysis demonstrated more balanced atomic displacement and highly correlated motions in the Holo system. The rationale for structural disparity observed in the disulfide bond formation and R143 configuration in Apo and Holo systems were elucidated using distance and dihedral probability distribution analyses.

CONCLUSION

Our study highlights the efficiency of combining extensive MD simulations with network analyses to unravel the features of protein allostery.

AlphaFold2-Enabled Atomistic Modeling of Epistatic Binding Mechanisms for the SARS-CoV-2 Spike Omicron XBB.1.5, EG.5 and FLip Variants: Convergent Evolution Hotspots Cooperate to Control Stability and Conformational Adaptability in Balancing ACE2 Binding and Antibody Resistance

In this study, we combined AI-based atomistic structural modeling and microsecond molecular simulations of the SARS-CoV-2 Spike complexes with the host receptor ACE2 for XBB.1.5+L455F, XBB.1.5+F456L(EG.5) and XBB.1.5+L455F/F456L (FLip) lineages to examine the mechanisms underlying the role of convergent evolution hotspots in balancing ACE2 binding and antibody evasion. Using the ensemble-based mutational scanning of the spike protein residues and physics-based rigorous computations of binding affinities, we identified binding energy hotspots and characterized molecular basis underlying epistatic couplings between convergent mutational hotspots. Consistent with the experiments, the results revealed the mediating role of Q493 hotspot in synchronization of epistatic couplings between L455F and F456L mutations providing a quantitative insight into the mechanism underlying differences between XBB lineages. Mutational profiling is combined with network-based model of epistatic couplings showing that the Q493, L455 and F456 sites mediate stable communities at the binding interface with ACE2 and can serve as stable mediators of non-additive couplings. Structure-based mutational analysis of Spike protein binding with the class 1 antibodies quantified the critical role of F456L and F486P mutations in eliciting strong immune evasion response. The results of this analysis support a mechanism in which the emergence of EG.5 and FLip variants may have been dictated by leveraging strong epistatic effects between several convergent revolutionary hotspots that provide synergy between the improved ACE2 binding and broad neutralization resistance. This interpretation is consistent with the notion that functionally balanced substitutions which simultaneously optimize immune evasion and high ACE2 affinity may continue to emerge through lineages with beneficial pair or triplet combinations of RBD mutations involving mediators of epistatic couplings and sites in highly adaptable RBD regions.

In silico design of a lipid-like compound targeting KRAS4B-G12D through non-covalent bonds

One of the most common drivers in human cancer is the peripheral membrane protein KRAS4B, able to promote oncogenic signalling. To signal, oncogenic KRAS4B not only requires a sufficient nucleotide exchange, but also needs to recruit effectors by exposing its effector-binding sites while anchoring to the phospholipid bilayer where KRAS4B-mediated signalling events occur. The enzyme phosphodiesterase-δ plays an important role in sequestering KRAS4B from the cytoplasm and targeting it to cellular membranes of different cell species. In this work, we present an in silico design of a lipid-like compound that has the remarkable feature of being able to target both an oncogenic KRAS4B-G12D mutant and the phosphodiesterase-δ enzyme. This double action is accomplished by adding a lipid tail (analogous to the farnesyl group of the KRAS4B protein) to an previously known active compound (2H-1,2,4-benzothiadiazine, 3,4-dihydro-,1,1-dioxide). The proposed lipid-like molecule was found to lock KRAS4B-G12D in its GDP-bound state by adjusting the effector-binding domain to be blocked by the interface of the lipid bilayer. Meanwhile, it can tune GTP-bound KRAS4B-G12D to shift from the active orientation state to the inactive state. The proposed compound is also observed to stably accommodate itself in the prenyl-binding pocket of phosphodiesterase-δ, which impairs KRAS4B enrichment at the lipid bilayer, potentially reducing the proliferation of KRAS4B inside the cytoplasm and its anchoring at the bilayer. In conclusion, we report a potential inhibitor of KRAS4B-G12D with a lipid tail attached to a specific warhead, a compound which has not yet been considered for drugs targeting RAS mutants. Our work provides new ways to target KRAS4B-G12D and can also foster drug discovery efforts for the targeting of oncogenes of the RAS family and beyond.

Allosteric inhibition of myosin by phenamacril: a synergistic mechanism revealed by computational and experimental approaches

BACKGROUND

Myosin plays a crucial role in cellular processes, while its dysfunction can lead to organismal malfunction. Phenamacril (PHA), a highly species-specific and non-competitive inhibitor of myosin I (FgMyoI) from Fusarium graminearum, has been identified as an effective fungicide for controlling plant diseases caused by partial Fusarium pathogens, such as wheat scab and rice bakanae. However, the molecular basis of its action is still unclear.

RESULTS

This study used multiple computational approaches first to elucidate the allosteric inhibition mechanism of FgMyoI by PHA at the atomistic level. The results indicated the increase of adenosine triphosphate (ATP) binding affinity upon PHA binding, which might impede the release of hydrolysis products. Furthermore, simulations revealed a broadened outer cleft and a significantly more flexible interface for actin binding, accompanied by a decrease in signaling transduction from the catalytic center to the actin-binding interface. These various effects might work together to disrupt the actomyosin cycle and hinder the ability of motor to generate force. Our experimental results further confirmed that PHA reduces the enzymatic activity of myosin and its binding with actin.

CONCLUSION

Therefore, our findings demonstrated that PHA might suppress the function of myosin through a synergistic mechanism, providing new insights into myosin allostery and offering new avenues for drug/fungicide discovery targeting myosin. © 2023 Society of Chemical Industry.

Exploring the molecular mechanism of cold-adaption of an alkaline protease mutant by molecular dynamics simulations and residue interaction network

Psychrophilic proteases have attracted enormous attention in past decades, due to their high catalytic activity at low temperatures in a wide range of industrial processes, especially in the detergent and leather industries. Among them, H5 is an alkaline protease mutant, which featuring psychrophilic-like behavior, but the reasons that H5 with higher activity at low temperatures are still poorly understood. Herein, the molecular dynamics (MD) simulations combined with residue interaction network (RIN) were utilized to investigate the mechanisms of the cold-adaption of mutant H5. The results demonstrated that two loops involved in the substrate binding G100-S104 and S125-S129 in H5 had higher mobility, and the distance enlargement between the two loops modulated the substrate's accessibility compared with wild type counterpart. Besides, H5 enhanced conformational flexibility by weakening salt bridges and increasing interaction with the solvent. In particular, the absence of Lys251-Asp197-Arg247 salt bridge network may contribute to the structural mobility. Based on the free energy landscape and molecular mechanics Poisson-Boltzmann surface area of the wild type and H5, it was elucidated that H5 possessed a large population of interconvertible conformations, resulting in the weaker substrate binding free energy. The calculated RIN topology parameters such as the average degree, average cluster coefficient, and average path length further verified that the mutant H5 attenuated residue-to-residue interactions. The investigation of the mechanisms by which how the residue mutation affects the stability and activity of enzymes provides a theoretical basis for the development of cold-adapted protease.

Computing allostery: from the understanding of biomolecular regulation and the discovery of cryptic sites to molecular design

The concept of allostery has become a central tenet in the study of biological systems. In parallel, the discovery of allosteric drugs is generating new opportunities to selectively modulate difficult targets involved in pathologic mechanisms. Molecular simulations can provide atomistically detailed insight into the processes involved in allosteric regulation and signaling, and at the same time, they have the potential to unveil regulatory hotspots or cryptic sites that are not immediately evident from the analysis of static structures. In this context, computational approaches should be able to connect the study of allosteric regulation at different scales to the possibility of leveraging this knowledge to expand the chemical space of new, active drugs. Here, we will discuss recent advances in the study of allosteric regulation via computational methods and connect the mechanistic knowledge generated to the possibility of designing new small molecules that can tweak the functions of their receptors.

Insight into the conserved structural dynamics of the C-terminus of mammal PrPC identifies structural core and possible structural role of pharmacological chaperones

Misfolding of the prion protein is central to prion disease aetiology. Although understanding the dynamics of the native fold helps to decipher the conformational conversion mechanism, a complete depiction of distal but coupled prion protein sites common across species is lacking. To fill this gap, we used normal mode analysis and network analysis to examine a collection of prion protein structures deposited on the protein data bank. Our study identified a core of conserved residues that sustains the connectivity across the C-terminus of the prion protein. We propose how a well-characterized pharmacological chaperone may stabilize the fold. Also, we provide insight into the effect on the native fold of initial misfolding pathways identified by others using kinetics studies.

RNet: a network strategy to predict RNA binding preferences

Determining the RNA binding preferences remains challenging because of the bottleneck of the binding interactions accompanied by subtle RNA flexibility. Typically, designing RNA inhibitors involves screening thousands of potential candidates for binding. Accurate binding site information can increase the number of successful hits even with few candidates. There are two main issues regarding RNA binding preference: binding site prediction and binding dynamical behavior prediction. Here, we propose one interpretable network-based approach, RNet, to acquire precise binding site and binding dynamical behavior information. RNetsite employs a machine learning-based network decomposition algorithm to predict RNA binding sites by analyzing the local and global network properties. Our research focuses on large RNAs with 3D structures without considering smaller regulatory RNAs, which are too small and dynamic. Our study shows that RNetsite outperforms existing methods, achieving precision values as high as 0.701 on TE18 and 0.788 on RB9 tests. In addition, RNetsite demonstrates remarkable robustness regarding perturbations in RNA structures. We also developed RNetdyn, a distance-based dynamical graph algorithm, to characterize the interface dynamical behavior consequences upon inhibitor binding. The simulation testing of competitive inhibitors indicates that RNetdyn outperforms the traditional method by 30%. The benchmark testing results demonstrate that RNet is highly accurate and robust. Our interpretable network algorithms can assist in predicting RNA binding preferences and accelerating RNA inhibitor design, providing valuable insights to the RNA research community.

Unmasking an Allosteric Binding Site of the Papain-like Protease in SARS-CoV-2: Molecular Dynamics Simulations of Corticosteroids

To date, mechanistic insights into many clinical drugs against COVID-19 remain unexplored. Dexamethasone, a corticosteroid, is one of them. While treating the entire corticosteroid database, including vitamins D2 and D3, with cutting-edge computational techniques, several intriguing results are unfolded. From the top-notch candidates, dexamethasone is likely to inhibit the viral main protease (Mpro), with vitamin D3 exhibiting multitarget [Mpro, papain-like protease (PLpro), and nucleocapsid protein (N-pro)] roles and ciclesonide's dynamic flipping disinterring a cryptic allosteric site in the PLpro enzyme. The results rationalize why these drugs improve the health of COVID-19 patients. Understanding an enzyme's secret binding site is essential to understanding how the enzyme works and how to inhibit its function. Ciclesonide's allosteric inhibition could not only jeopardize PLpro's catalytic role in polyprotein processing but also make it less vulnerable to the host body's defense machinery. Hotspot residues in the identified allosteric site could be considered for effective therapeutic designs against PLpro.

Molecular dynamics simulation study on Bacillus subtilis EngA: the presence of Mg2+ at the active-sites promotes the functionally important conformation

EngA, a GTPase contains two GTP binding domains [GD1, GD2], and the C-terminal KH domain shown to be involved in the later stages of ribosome maturation. Association of EngA to the ribosomal subunit in the intermediate stage of maturation is essential for complete ribosome maturation. However, this association was shown to be dependent on the nucleotide bound combinations. This nucleotide dependent association tendency is attributed to the conformational changes that occur among different nucleotide bound combinations. Therefore, to explore the conformational changes, all-atom molecular dynamics simulations for Bacillus subtilis EngA in different nucleotide bound combinations along with the presence or absence of Mg2+ in the active-sites were carried out. The presence of Mg2+ along with the bound nucleotide at the GD2 active-site dictates the GD2-Sw-II mobility, but the GD1-Sw-II mobility has not shown any nucleotide or Mg2+ dependent movement. However, the GD1-Sw-II secondary conformations are shown to be influenced by the GD2 nucleotide bound state. This allosteric connection between the GD2 active-site and the GD1-Sw-II is also observed through the dynamic network analysis. Further, the exploration of the GD1-KH interface interactions exhibited a more attractive tendency when GD1 is bound to GTP-Mg2+. In addition, the presence of Mg2+ stabilizes active-site water and also increases the distances between the α- and γ- phosphates of the bound GTP. Curiously, three water molecules in the GD1 active-site and only one water molecule in the GD2 active-site are stabilized. This indicates that the probability of GTP hydrolysis is more in GD1 compared to GD2.Communicated by Ramaswamy H. Sarma.

Structure, dynamics and free energy studies on the effect of point mutations on SARS-CoV-2 spike protein binding with ACE2 receptor

The ongoing COVID-19 pandemic continues to infect people worldwide, and the virus continues to evolve in significant ways which can pose challenges to the efficiency of available vaccines and therapeutic drugs and cause future pandemic. Therefore, it is important to investigate the binding and interaction of ACE2 with different RBD variants. A comparative study using all-atom MD simulations was conducted on ACE2 binding with 8 different RBD variants, including N501Y, E484K, P479S, T478I, S477N, N439K, K417N and N501Y-E484K-K417N on RBD. Based on the RMSD, RMSF, and DSSP results, overall the binding of RBD variants with ACE2 is stable, and the secondary structure of RBD and ACE2 are consistent after the point mutation. Besides that, a similar buried surface area, a consistent binding interface and a similar amount of hydrogen bonds formed between RBD and ACE2 although the exact residue pairs on the binding interface were modified. The change of binding free energy from point mutation was predicted using the free energy perturbation (FEP) method. It is found that N501Y, N439K, and K417N can strengthen the binding of RBD with ACE2, while E484K and P479S weaken the binding, and S477N and T478I have negligible effect on the binding. Point mutations modified the dynamic correlation of residues in RBD based on the dihedral angle covariance matrix calculation. Doing dynamic network analysis, a common intrinsic network community extending from the tail of RBD to central, then to the binding interface region was found, which could communicate the dynamics in the binding interface region to the tail thus to the other sections of S protein. The result can supply unique methodology and molecular insight on studying the molecular structure and dynamics of possible future pandemics and design novel drugs.

Kinetic and thermodynamic allostery in the Ras protein family

Allostery, the transfer of information between distant parts of a macromolecule, is a fundamental feature of protein function and regulation. However, allosteric mechanisms are usually not explained by protein structure, requiring information on correlated fluctuations uniquely accessible to molecular simulation. Existing work to extract allosteric pathways from molecular dynamics simulations has focused on thermodynamic correlations. Here, we show how kinetic correlations encode complementary information essential to explain observed variations in allosteric regulation. We applied kinetic and thermodynamic correlation analysis on atomistic simulations of H, K, and NRas isoforms in the apo, GTP, and GDP-bound states of Ras protein, with and without complexing to its downstream effector, Raf. We show that switch I and switch II are the primary components of thermodynamic and kinetic allosteric networks, consistent with the key roles of these two motifs. These networks connect the switches to an allosteric loop recently discovered from a crystal structure of HRas. This allosteric loop is inactive in KRas, but is coupled to the hydrolysis arm switch II in NRas and HRas. We find that the mechanism in the latter two isoforms are thermodynamic and kinetic, respectively. Binding of Raf-RBD further activates thermodynamic allostery in HRas and KRas but has limited effect on NRas. These results indicate that kinetic and thermodynamic correlations are both needed to explain protein function and allostery. These two distinct channels of allosteric regulation, and their combinatorial variability, may explain how subtle mutational differences can lead to diverse regulatory profiles among enzymatic proteins.