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.

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).

Elastic network model reveals distinct flexibilities of capping proteins bound to CARMIL and twinfilin-tail

Capping protein (CP) binds to the barbed end of an actin-filament and inhibits its elongation. CARMIL binds CP and dissociates it from the barbed end of the actin-filament. The binding of CARMIL peptide alters the flexibility of CP, which is considered to facilitate the dissociation. Twinfilin also binds to CP through its C-terminal tail. The complex structures of the CP/twinfilin-tail (TW-tail) peptide indicate that the binding sites of CARMIL and TW-tail overlap. However, TW-tail binding does not facilitate the dissociation of CP from the barbed end. We extensively investigated the flexibilities of CP in the CP/TW-tail or CP/CARMIL complexes using an elastic network model and concluded that TW-tail binding does not alter the flexibility of CP. Our extensive analysis also highlighted that the strong contacts of peptides with the two domains of CP, that is, the CP-L and CP-S domains, are key to changing the flexibilities of CP. CARMIL peptides can interact strongly with both of the domains, while TW-tail peptides exclusively interact with the CP-S domain because the binding site of TW-tail on CP relatively shifts to the CP-S domain compared with that of CP/CARMIL. This result supports our hypothesis that the dissociation of CP from the barbed end is regulated by the flexibility of CP.

Screening of phytochemicals from Clerodendrum inerme (L.) Gaertn as potential anti-breast cancer compounds targeting EGFR: an in-silico approach

Breast cancer (BC) is the most prevalent malignancy among women around the world. The epidermal growth factor receptor (EGFR) is a tyrosine kinase receptor (RTK) of the ErbB/HER family. It is essential for triggering the cellular signaling cascades that control cell growth and survival. However, perturbations in EGFR signaling lead to cancer development and progression. Hence, EGFR is regarded as a prominent therapeutic target for breast cancer. Therefore, in the current investigation, EGFR was targeted with phytochemicals from Clerodendrum inerme (L.) Gaertn (C. inerme). A total of 121 phytochemicals identified by gas chromatography-mass spectrometry (GC-MS) analysis were screened against EGFR through molecular docking, ADMET analyses (Absorption, Distribution, Metabolism, Excretion, and Toxicity), PASS predictions, and molecular dynamics simulation, which revealed three potential hit compounds with CIDs 10586 [i.e. alpha-bisabolol (-6.4 kcal/mol)], 550281 [i.e. 2,(4,4-Trimethyl-3-hydroxymethyl-5a-(3-methyl-but-2-enyl)-cyclohexene) (-6.5 kcal/mol)], and 161271 [i.e. salvigenin (-7.4 kcal/mol)]. The FDA-approved drug gefitinib was used to compare the inhibitory effects of the phytochemicals. The top selected compounds exhibited good ADMET properties and obeyed Lipinski's rule of five (ROF). The molecular docking analysis showed that salvigenin was the best among the three compounds and formed bonds with the key residue Met 793. Furthermore, the molecular mechanics generalized born surface area (MMGBSA) calculations, molecular dynamics simulation, and normal mode analysis validated the binding affinity of the compounds and also revealed the strong stability and compactness of phytochemicals at the docked site. Additionally, DFT and DOS analyses were done to study the reactivity of the compounds and to further validate the selected phytochemicals. These results suggest that the identified phytochemicals possess high inhibitory potential against the target EGFR and can treat breast cancer. However, further in vitro and in vivo investigations are warranted towards the development of these constituents into novel anti-cancer drugs.Communicated by Ramaswamy H. Sarma.

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.

Comparative analysis of permanent and transient domain-domain interactions in multi-domain proteins

Protein domains are structural, functional, and evolutionary units. These domains bring out the diversity of functionality by means of interactions with other co-existing domains and provide stability. Hence, it is important to study intra-protein inter-domain interactions from the perspective of types of interactions. Domains within a chain could interact over short timeframes or permanently, rather like protein-protein interactions (PPIs). However, no systematic study has been carried out between two classes, namely permanent and transient domain-domain interactions. In this work, we studied 263 two-domain proteins, belonging to either of these classes and their interfaces on the basis of several factors, such as interface area and details of interactions (number, strength, and types of interactions). We also characterized them based on residue conservation at the interface, correlation of residue motions across domains, its involvement in repeat formation, and their involvement in particular molecular processes. Finally, we could analyze the interactions arising from domains in two-domain monomeric proteins, and we observed significant differences between these two classes of domain interactions and a few similarities. This study will help to obtain a better understanding of structure-function and folding principles of multi-domain proteins.

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.

In silico study of cox protein from P2 type enteric bacteriophages based on sequence, structure and dynamics to understand its functional integrity

Cox protein plays a critical role in deciding the lytic-lysogenic switch of P2 enteric phages. This phenomenon makes Cox protein one of the most important candidates in developing novel phage-based therapeutics against antibacterial resistant pathogens. The principle focus concerning protein and its decision making is a DNA binding event, which helps to regulate differential promoter expression. In the current study, we have attempted to understand the sequence, structural and dynamic features associated with Cox protein and its DNA binding. Unavailability of information was a big burden in further proceedings. We have done an extensive literature search to develop a database of Cox with relevant information. That information coupled with the methods of Sequence-based phylogenetic and conservation studies, Homology Modelling, Atomic-level Docking and Molecular Dynamics (MD) Simulation (50 ns each for 10 systems, i.e. total of 500 ns) were performed in the current study. Analysis of those extensive studies has provided us the required sequence to structure to dynamics to functional understanding. Our present study would indeed be very helpful in understanding the biochemical mechanism of Cox activation as well as designing potential phage therapeutics.

Molecular simulation unravels the amyloidogenic misfolding of nascent ApoA1 protein, driven by deleterious point mutations occurring in between 170-178 hotspot region

Protein ApoA1 is extensively studied for its role in lipid metabolism. Its seedy dark side of amyloid formulation remains relatively understudied yet. Due to genetic mutations, the protein pathologically misshapes into its amyloid form that gets accumulated in various organs, including the heart. To contrive effective therapeutics against this debilitating congenital disorder, it is imperative to comprehend the structural ramifications induced by mutations in APoA1's dynamic conformation. Till now, several point mutations have been implicated in ApoA1's amyloidosis, although only a handful has been examined considerably. Especially, the single nucleotide polymorphisms (SNPs) that occur in-between 170-178 mutation hotspot site of APoA1 needs to be investigated, since most of them are culpable of amyloid deposition in the heart. To that effect, in the present study, we have computationally quantified and studied the ApoA1's biomolecular modifications fostered by SNPs in the 170-178 mutation hotspot. Findings from discrete molecular dynamics simulation studies indicate that the SNPs have noticeably steered the ApoA1's behaviour from its native structural dynamics. Analysis of protein's secondary structural changes exhibits a considerable change upon mutations. Further, subjecting the protein structures to simulated thermal denaturation shows increased resistance to denaturation among mutants when compared to native. Further, normal mode analysis of protein's dynamic motion also shows discrepancy in its dynamic structural change upon SNP. These structural digressions induced by SNPs can very well be the biomolecular incendiary that drives ApoA1 into its amyloidogenesis. And, understanding these structural modifications initiates a better understanding of SNP's amyloidogenic pathology on APoA1.Communicated by Ramaswamy H. Sarma.

Molecular mechanism of ATP and RNA binding to Zika virus NS3 helicase and identification of repurposed drugs using molecular dynamics simulations

Congenital Zika virus syndrome has caused a public health emergency of international concern. So far, there are no drugs available to prevent or treat the infection caused by Zika virus. The Zika virus NS3 helicase is a potential protein target for drug discovery due to its vital role in viral genome replication. NS3 helicase unwinds the viral RNA to enable the reproduction of the viral genome by the NS5 protein. NS3 helicase has two crucial binding sites; the ATP binding site and the RNA binding site. We used molecular docking and molecular dynamics (MD) simulations to study the structural behavior of Zika virus NS3 helicase in its apo form and in the presence of ATP, single-stranded RNA, and both ATP-RNA to understand their potential implications in NS3 helicase activity. Further, we have carried out virtual screening of FDA approved drugs, followed by molecular docking to identify the ATP-competitive hit molecules as probable Zika virus NS3 helicase inhibitors. The MD simulations trajectories were analyzed using normal mode analysis and principal component analysis that reveals fluctuations in the R-loop. These findings aid in understanding the molecular mechanisms of the simultaneous binding of ATP and RNA, and guide the design and discovery of new inhibitors of the Zika virus NS3 helicase as a promising drug target to treat the Zika virus infection. Communicated by Ramaswamy H. Sarma.

Engineering Modified mRNA-Based Vaccine against Dengue Virus Using Computational and Reverse Vaccinology Approaches

Dengue virus belonging to the family Flaviviridae and its four serotypes are responsible for dengue infections, which extend over 60 countries in tropical and subtropical areas of the world including Pakistan. During the ongoing dengue outbreak in Pakistan (2022), over 30,000 cases have been reported, and over 70 lives have been lost. The only commercialized vaccine against DENV, Dengvaxia, cannot be administered as a prophylactic measure to cure this infection due to various complications. Using machine learning and reverse vaccinology approaches, this study was designed to develop a tetravalent modified nucleotide mRNA vaccine using NS1, prM, and EIII sequences of dengue virus from Pakistani isolates. Based on high antigenicity, non-allergenicity, and toxicity profiling, B-cell epitope, cytotoxic T lymphocyte (CTL), and helper T lymphocyte (HTL) putative vaccine targets were predicted. Molecular docking confirmed favorable interactions between T-cell epitopes and their respective HLA alleles, while normal mode analysis validated high-affinity interactions of vaccine proteins with immune receptors. In silico immune simulations confirmed adequate immune responses to eliminate the antigen and generate memory. Codon optimization, physicochemical features, nucleotide modifications, and suitable vector availability further ensured better antigen expression and adaptive immune responses. We predict that this vaccine construct may prove to be a good vaccinal candidate against dengue virus in vitro as well.

The Statistical Trends of Protein Evolution: A Lesson from AlphaFold Database

The recent development of artificial intelligence provides us with new and powerful tools for studying the mysterious relationship between organism evolution and protein evolution. In this work, based on the AlphaFold Protein Structure Database (AlphaFold DB), we perform comparative analyses of the proteins of different organisms. The statistics of AlphaFold-predicted structures show that, for organisms with higher complexity, their constituent proteins will have larger radii of gyration, higher coil fractions, and slower vibrations, statistically. By conducting normal mode analysis and scaling analyses, we demonstrate that higher organismal complexity correlates with lower fractal dimensions in both the structure and dynamics of the constituent proteins, suggesting that higher functional specialization is associated with higher organismal complexity. We also uncover the topology and sequence bases of these correlations. As the organismal complexity increases, the residue contact networks of the constituent proteins will be more assortative, and these proteins will have a higher degree of hydrophilic-hydrophobic segregation in the sequences. Furthermore, by comparing the statistical structural proximity across the proteomes with the phylogenetic tree of homologous proteins, we show that, statistical structural proximity across the proteomes may indirectly reflect the phylogenetic proximity, indicating a statistical trend of protein evolution in parallel with organism evolution. This study provides new insights into how the diversity in the functionality of proteins increases and how the dimensionality of the manifold of protein dynamics reduces during evolution, contributing to the understanding of the origin and evolution of lives.

Computational studies on the design of NCI natural products as inhibitors to SARS-CoV-2 main protease

The pandemic coronavirus disease (COVID-19) caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has resulted in more than 5 million deaths globally. Currently there are no effective drugs available to treat COVID-19. The viral protease replication can be blocked by the inhibition of main protease that is encoded in polyprotein 1a and is therefore a potential protein target for drug discovery. We have carried out virtual screening of NCI natural compounds followed by molecular docking in order to identify hit molecules as probable SARS-CoV-2 main protease inhibitors. The molecular dynamics (MD) simulations of apo form in complex with N3, α-ketoamide and NCI natural products was used to validate the screened compounds. The MD simulations trajectories were analyzed using normal mode analysis and principal component analysis revealing dynamical nature of the protein. These findings aid in understanding the binding of natural products and molecular mechanisms of SARS-CoV-2 main protease inhibition.Communicated by Ramaswamy H. Sarma.

Site Density Functional Theory and Structural Bioinformatics Analysis of the SARS-CoV Spike Protein and hACE2 Complex

The entry of the SARS-CoV-2, a causative agent of COVID-19, into human host cells is mediated by the SARS-CoV-2 spike (S) glycoprotein, which critically depends on the formation of complexes involving the spike protein receptor-binding domain (RBD) and the human cellular membrane receptor angiotensin-converting enzyme 2 (hACE2). Using classical site density functional theory (SDFT) and structural bioinformatics methods, we investigate binding and conformational properties of these complexes and study the overlooked role of water-mediated interactions. Analysis of the three-dimensional reference interaction site model (3DRISM) of SDFT indicates that water mediated interactions in the form of additional water bridges strongly increases the binding between SARS-CoV-2 spike protein and hACE2 compared to SARS-CoV-1-hACE2 complex. By analyzing structures of SARS-CoV-2 and SARS-CoV-1, we find that the homotrimer SARS-CoV-2 S receptor-binding domain (RBD) has expanded in size, indicating large conformational change relative to SARS-CoV-1 S protein. Protomer with the up-conformational form of RBD, which binds with hACE2, exhibits stronger intermolecular interactions at the RBD-ACE2 interface, with differential distributions and the inclusion of specific H-bonds in the CoV-2 complex. Further interface analysis has shown that interfacial water promotes and stabilizes the formation of CoV-2/hACE2 complex. This interaction causes a significant structural rigidification of the spike protein, favoring proteolytic processing of the S protein for the fusion of the viral and cellular membrane. Moreover, conformational dynamics simulations of RBD motions in SARS-CoV-2 and SARS-CoV-1 point to the role in modification of the RBD dynamics and their impact on infectivity.

Pseudokinases repurpose flexibility signatures associated with the protein kinase fold for noncatalytic roles

The bilobal protein kinase-like fold in pseudokinases lack one or more catalytic residues, conserved in canonical protein kinases, and are considered enzymatically deficient. Tertiary structures of pseudokinases reveal that their loops topologically equivalent to activation segments of kinases adopt contracted configurations, which is typically extended in active conformation of kinases. Herein, anisotropic network model based normal mode analysis (NMA) was conducted on 51 active conformation structures of protein kinases and 26 crystal structures of pseudokinases. Our observations indicate that although backbone fluctuation profiles are similar for individual kinase-pseudokinase families, low intensity mean square fluctuations in pseudo-activation segment and other sub-structures impart rigidity to pseudokinases. Analyses of collective motions from functional modes reveal that pseudokinases, compared to active kinases, undergo distinct conformational transitions using the same structural fold. All-atom NMA of protein kinase-pseudokinase pairs from each family, sharing high amino acid sequence identities, yielded distinct community clusters, partitioned by residues exhibiting highly correlated fluctuations. It appears that atomic fluctuations from equivalent activation segments guide community membership and network topologies for respective kinase and pseudokinase. Our findings indicate that such adaptations in backbone and side-chain fluctuations render pseudokinases competent for catalysis-independent roles.

Interpretation of Single-Molecule Force Experiments on Proteins Using Normal Mode Analysis

Single-molecule force spectroscopy experiments allow protein folding and unfolding to be explored using mechanical force. Probably the most informative technique for interpreting the results of these experiments at the structural level makes use of steered molecular dynamics (MD) simulations, which can explicitly model the protein under load. Unfortunately, this technique is computationally expensive for many of the most interesting biological molecules. Here, we find that normal mode analysis (NMA), a significantly cheaper technique from a computational perspective, allows at least some of the insights provided by MD simulation to be gathered. We apply this technique to three non-homologous proteins that were previously studied by force spectroscopy: T4 lysozyme (T4L), Hsp70 and the glucocorticoid receptor domain (GCR). The NMA results for T4L and Hsp70 are compared with steered MD simulations conducted previously, and we find that we can recover the main results. For the GCR, which did not undergo MD simulation, our approach identifies substructures that correlate with experimentally identified unfolding intermediates. Overall, we find that NMA can make a valuable addition to the analysis toolkit for the structural analysis of single-molecule force experiments on proteins.

Comparative Analysis of Structural and Dynamical Features of Ribosome Upon Association With mRNA Reveals Potential Role of Ribosomal Proteins

Ribosomes play a critical role in maintaining cellular proteostasis. The binding of messenger RNA (mRNA) to the ribosome regulates kinetics of protein synthesis. To generate an understanding of the structural, mechanistic, and dynamical features of mRNA recognition in the ribosome, we have analysed mRNA-protein interactions through a structural comparison of the ribosomal complex in the presence and absence of mRNA. To do so, we compared the 3-Dimensional (3D) structures of components of the two assembly structures and analysed their structural differences because of mRNA binding, using elastic network models and structural network-based analysis. We observe that the head region of 30S ribosomal subunit undergoes structural displacement and subunit rearrangement to accommodate incoming mRNA. We find that these changes are observed in proteins that lie far from the mRNA-protein interface, implying allostery. Further, through perturbation response scanning, we show that the proteins S13, S19, and S20 act as universal sensors that are sensitive to changes in the inter protein network, upon binding of 30S complex with mRNA and other initiation factors. Our study highlights the significance of mRNA binding in the ribosome complex and identifies putative allosteric sites corresponding to alterations in structure and/or dynamics, in regions away from mRNA binding sites in the complex. Overall, our work provides fresh insights into mRNA association with the ribosome, highlighting changes in the interactions and dynamics of the ribosome assembly because of the binding.

HEMNMA-3D: Cryo Electron Tomography Method Based on Normal Mode Analysis to Study Continuous Conformational Variability of Macromolecular Complexes

Cryogenic electron tomography (cryo-ET) allows structural determination of biomolecules in their native environment (in situ). Its potential of providing information on the dynamics of macromolecular complexes in cells is still largely unexploited, due to the challenges of the data analysis. The crowded cell environment and continuous conformational changes of complexes make difficult disentangling the data heterogeneity. We present HEMNMA-3D, which is, to the best of our knowledge, the first method for analyzing cryo electron subtomograms in terms of continuous conformational changes of complexes. HEMNMA-3D uses a combination of elastic and rigid-body 3D-to-3D iterative alignments of a flexible 3D reference (atomic structure or electron microscopy density map) to match the conformation, orientation, and position of the complex in each subtomogram. The elastic matching combines molecular mechanics simulation (Normal Mode Analysis of the 3D reference) and experimental, subtomogram data analysis. The rigid-body alignment includes compensation for the missing wedge, due to the limited tilt angle of cryo-ET. The conformational parameters (amplitudes of normal modes) of the complexes in subtomograms obtained through the alignment are processed to visualize the distribution of conformations in a space of lower dimension (typically, 2D or 3D) referred to as space of conformations. This allows a visually interpretable insight into the dynamics of the complexes, by calculating 3D averages of subtomograms with similar conformations from selected (densest) regions and by recording movies of the 3D reference's displacement along selected trajectories through the densest regions. We describe HEMNMA-3D and show its validation using synthetic datasets. We apply HEMNMA-3D to an experimental dataset describing in situ nucleosome conformational variability. HEMNMA-3D software is available freely (open-source) as part of ContinuousFlex plugin of Scipion V3.0 (http://scipion.i2pc.es).

A unique ligand-steered strategy for CC chemokine receptor 2 homology modeling to facilitate structure-based virtual screening

CC chemokine receptor 2 (CCR2) antagonists that disrupt CCR2/MCP-1 interaction are expected to treat a variety of inflammatory and autoimmune diseases. The lack of CCR2 crystal structure limits the application of structure-based drug design (SBDD) to this target. Although a few three-dimensional theoretical models have been reported, their accuracy remains to be improved in terms of templates and modeling approaches. In this study, we developed a unique ligand-steered strategy for CCR2 homology modeling. It starts with an initial model based on the X-ray structure of the closest homolog so far, that is, CXCR4. Then, it uses Elastic Network Normal Mode Analysis (EN-NMA) and flexible docking (FD) by AutoDock Vina software to generate ligand-induced fit models. It selects optimal model(s) as well as scoring function(s) via extensive evaluation of model performance based on a unique benchmarking set constructed by our in-house tool, that is, MUBD-DecoyMaker. The model of 81_04 presents the optimal enrichment when combined with the scoring function of PMF04, and the proposed binding mode between CCR2 and Teijin lead by this model complies with the reported mutagenesis data. To highlight the advantage of our strategy, we compared it with the only reported ligand-steered strategy for CCR2 homology modeling, that is, Discovery Studio/Ligand Minimization. Lastly, we performed prospective virtual screening based on 81_04 and CCR2 antagonist bioassay. The identification of two hit compounds, that is, E859-1281 and MolPort-007-767-945, validated the efficacy of our model and the ligand-steered strategy.

Predicting cryptic ligand binding sites based on normal modes guided conformational sampling

To greatly expand the druggable genome, fast and accurate predictions of cryptic sites for small molecules binding in target proteins are in high demand. In this study, we have developed a fast and simple conformational sampling scheme guided by normal modes solved from the coarse-grained elastic models followed by atomistic backbone refinement and side-chain repacking. Despite the observations of complex and diverse conformational changes associated with ligand binding, we found that simply sampling along each of the lowest 30 modes is near optimal for adequately restructuring cryptic sites so they can be detected by existing pocket finding programs like fpocket and concavity. We further trained machine-learning protocols to optimize the combination of the sampling-enhanced pocket scores with other dynamic and conservation scores, which only slightly improved the performance. As assessed based on a training set of 84 known cryptic sites and a test set of 14 proteins, our method achieved high accuracy of prediction (with area under the receiver operating characteristic curve >0.8) comparable to the CryptoSite server. Compared with CryptoSite and other methods based on extensive molecular dynamics simulation, our method is much faster (1-2 hours for an average-size protein) and simpler (using only pocket scores), so it is suitable for high-throughput processing of large datasets of protein structures at the genome scale.

D614G substitution at the hinge region enhances the stability of trimeric SARS-CoV-2 spike protein

Mutations in the spike protein of SARS-CoV-2 are the major causes for the modulation of ongoing COVID-19 infection. Currently, the D614G substitution in the spike protein has become dominant worldwide. It is associated with higher infectivity than the ancestral (D614)variant. We demonstrate using Gaussian network model-based normal mode analysis that the D614G substitution occurs at the hinge region that facilitates domain-domain motions between receptor binding domain and S2 region of the spike protein. Computer-aided mutagenesis and inter-residue energy calculations reveal that contacts involving D614 are energetically frustrated. However, contacts involving G614 are energetically favourable, implying the substitution strengthens residue contacts that are formed within as well as between protomers. We also find that the free energy difference (ΔΔG) between two variants is -2.6 kcal/mol for closed and -2.0 kcal/mol for 1-RBD up conformation. Thus, the thermodynamic stability has increased upon D614G substitution. Whereas the reverse mutation in spike protein structures having G614 substitution has resulted in the free energy differences of 6.6 kcal/mol and 6.3 kcal/mol for closed and 1-RBD up conformations, respectively, indicating that the overall thermodynamic stability has decreased. These results suggest that the D614G substitution modulates the flexibility of spike protein and confers enhanced thermodynamic stability irrespective of conformational states. This data concurs with the known information demonstrating increased availability of the functional form of spikeprotein trimer upon D614G substitution.

Novel RyR2 Mutation (G3118R) Is Associated With Autosomal Recessive Ventricular Fibrillation and Sudden Death: Clinical, Functional, and Computational Analysis

Background

The cardiac ryanodine receptor type 2 (RyR2) is a large homotetramer, located in the sarcoplasmic reticulum (SR), which releases Ca²⁺ from the SR during systole. The molecular mechanism underlying Ca²⁺ sensing and gating of the RyR2 channel in health and disease is only partially elucidated. Catecholaminergic Polymorphic Ventricular Tachycardia (CPVT1) is the most prevalent syndrome caused by RyR2 mutations.

Methods and Results

This study involves investigation of a family with 4 cases of ventricular fibrillation and sudden death and physiological tests in HEK 293 cells and normal mode analysis (NMA) computation. We found 4 clinically affected members who were homozygous for a novel RyR2 mutation, G3118R, whereas their heterozygous relatives are asymptomatic. G3118R is located in the periphery of the protein, far from the mutation hotspot regions. HEK293 cells harboring G3118R mutation inhibited Ca²⁺ release in response to increasing doses of caffeine, but decreased the termination threshold for store‐overload‐induced Ca²⁺ release, thus increasing the fractional Ca²⁺ release in response to increasing extracellular Ca²⁺. NMA showed that G3118 affects RyR2 tetramer in a dose‐dependent manner, whereas in the model of homozygous mutant RyR2, the highest entropic values are assigned to the pore and the central regions of the protein.

Conclusions

RyR2 G3118R is related to ventricular fibrillation and sudden death in recessive mode of inheritance and has an effect of gain of function on the protein. Despite a peripheral location, it has an allosteric effect on the stability of central and pore regions in a dose‐effect manner.

Structural Communication between the E. coli Chaperones DnaK and Hsp90

The 70 kDa and 90 kDa heat shock proteins Hsp70 and Hsp90 are two abundant and highly conserved ATP-dependent molecular chaperones that participate in the maintenance of cellular homeostasis. In Escherichia coli, Hsp90 (Hsp90Ec) and Hsp70 (DnaK) directly interact and collaborate in protein remodeling. Previous work has produced a model of the direct interaction of both chaperones. The locations of the residues involved have been confirmed and the model has been validated. In this study, we investigate the allosteric communication between Hsp90Ec and DnaK and how the chaperones couple their conformational cycles. Using elastic network models (ENM), normal mode analysis (NMA), and a structural perturbation method (SPM) of asymmetric and symmetric DnaK-Hsp90Ec, we extract biologically relevant vibrations and identify residues involved in allosteric signaling. When one DnaK is bound, the dominant normal modes favor biological motions that orient a substrate protein bound to DnaK within the substrate/client binding site of Hsp90Ec and release the substrate from the DnaK substrate binding domain. The presence of one DnaK molecule stabilizes the entire Hsp90Ec protomer to which it is bound. Conversely, the symmetric model of DnaK binding results in steric clashes of DnaK molecules and suggests that the Hsp90Ec and DnaK chaperone cycles operate independently. Together, this data supports an asymmetric binding of DnaK to Hsp90Ec.

Deciphering the Mechanism of Inhibition of SERCA1a by Sarcolipin Using Molecular Simulations

SERCA1a is an ATPase calcium pump that transports Ca²⁺ from the cytoplasm to the sarco/endoplasmic reticulum lumen. Sarcolipin (SLN), a transmembrane peptide, regulates the activity of SERCA1a by decreasing its Ca²⁺ transport rate, but its mechanism of action is still not well-understood. To decipher this mechanism, we have performed normal mode analysis in the all-atom model, with the SERCA1a-SLN complex, or the isolated SERCA1a, embedded in an explicit membrane. The comparison of the results allowed us to provide an explanation at the atomic level for the action of SLN that is in good agreement with experimental observations. In our analyses, the presence of SLN locally perturbs the TM6 transmembrane helix and as a consequence modifies the position of D800, one of the key metal-chelating residues. Additionally, it reduces the flexibility of the gating residues, V304, and E309 in TM4, at the entrance of the Ca²⁺ binding sites, which would decrease the affinity for Ca²⁺. Unexpectedly, SLN has also an effect on the ATP binding site more than 35 Å away, due to the straightening of TM5, a long helix considered as the spine of the protein. The straightening of TM5 modifies the structure of the P-N linker that sits above it, and which comprises the ³⁵¹DKTG³⁵⁴ conserved motif, resulting in an increase of the distance between ATP and the phosphorylation site. As a consequence, the turn-over rate could be affected. All this gives SERCA1a the propensity to go toward a Ca²⁺ low-affinity E2-like state in the presence of SLN and toward a Ca²⁺ high-affinity E1-like state in the absence of SLN. In addition to a general mechanism of inhibition of SERCA1a regulatory peptides, this study also provides an insight into the conformational transition between the E2 and E1 states.

D614G substitution at the hinge region enhances the stability of trimeric SARS-CoV-2 spike protein

Mutations in the spike protein of SARS-CoV-2 are the major causes for the modulation of ongoing COVID-19 infection. Currently, the D614G substitution in the spike protein has become dominant worldwide. It is associated with higher infectivity than the ancestral (D614)variant. We demonstrate using Gaussian network model-based normal mode analysis that the D614G substitution occurs at the hinge region that facilitates domain-domain motions between receptor binding domain and S2 region of the spike protein. Computer-aided mutagenesis and inter-residue energy calculations reveal that contacts involving D614 are energetically frustrated. However, contacts involving G614 are energetically favourable, implying the substitution strengthens residue contacts that are formed within as well as between protomers. We also find that the free energy difference (ΔΔG) between two variants is -2.6 kcal/mol for closed and -2.0 kcal/mol for 1-RBD up conformation. Thus, the thermodynamic stability has increased upon D614G substitution. Whereas the reverse mutation in spike protein structures having G614 substitution has resulted in the free energy differences of 6.6 kcal/mol and 6.3 kcal/mol for closed and 1-RBD up conformations, respectively, indicating that the overall thermodynamic stability has decreased. These results suggest that the D614G substitution modulates the flexibility of spike protein and confers enhanced thermodynamic stability irrespective of conformational states. This data concurs with the known information demonstrating increased availability of the functional form of spikeprotein trimer upon D614G substitution.

Using normal mode analysis on protein structural models. How far can we go on our predictions?

Normal mode analysis (NMA) is a fast and inexpensive approach that is largely used to gain insight into functional protein motions, and more recently to create conformations for further computational studies. However, when the protein structure is unknown, the use of computational models is necessary. Here, we analyze the capacity of NMA in internal coordinate space to predict protein motion, its intrinsic flexibility, and atomic displacements, using protein models instead of native structures, and the possibility to use it for model refinement. Our results show that NMA is quite insensitive to modeling errors, but that calculations are strictly reliable only for very accurate models. Our study also suggests that internal NMA is a more suitable tool for the improvement of structural models, and for integrating them with experimental data or in other computational techniques, such as protein docking or more refined molecular dynamics simulations.

Transient association between proteins elicits alteration of dynamics at sites far away from interfaces

Proteins are known to undergo structural changes upon binding to partner proteins. However, the prevalence, extent, location, and function of change in protein dynamics due to transient protein-protein interactions is not well documented. Here, we have analyzed a dataset of 58 protein-protein complexes of known three-dimensional structure and structures of their corresponding unbound forms to evaluate dynamics changes induced by binding. Fifty-five percent of cases showed significant dynamics change away from the interfaces. This change is not always accompanied by an observed structural change. Binding of protein partner is found to alter inter-residue communication within the tertiary structure in about 90% of cases. Also, residue motions accessible to proteins in unbound form were not always maintained in the bound form. Further analyses revealed functional roles for the distant site where dynamics change was observed. Overall, the results presented here strongly suggest that alteration of protein dynamics due to binding of a partner protein commonly occurs.

Structure and Function of the Human Ryanodine Receptors and Their Association with Myopathies-Present State, Challenges, and Perspectives

Cardiac arrhythmias are serious, life-threatening diseases associated with the dysregulation of Ca2+ influx into the cytoplasm of cardiomyocytes. This dysregulation often arises from dysfunction of ryanodine receptor 2 (RyR2), the principal Ca2+ release channel. Dysfunction of RyR1, the skeletal muscle isoform, also results in less severe, but also potentially life-threatening syndromes. The RYR2 and RYR1 genes have been found to harbor three main mutation “hot spots”, where mutations change the channel structure, its interdomain interface properties, its interactions with its binding partners, or its dynamics. In all cases, the result is a defective release of Ca2+ ions from the sarcoplasmic reticulum into the myocyte cytoplasm. Here, we provide an overview of the most frequent diseases resulting from mutations to RyR1 and RyR2, briefly review some of the recent experimental structural work on these two molecules, detail some of the computational work describing their dynamics, and summarize the known changes to the structure and function of these receptors with particular emphasis on their N-terminal, central, and channel domains.

The Bio3D packages for structural bioinformatics

Bio3D is a family of R packages for the analysis of biomolecular sequence, structure, and dynamics. Major functionality includes biomolecular database searching and retrieval, sequence and structure conservation analysis, ensemble normal mode analysis, protein structure and correlation network analysis, principal component, and related multivariate analysis methods. Here, we review recent package developments, including a new underlying segregation into separate packages for distinct analysis, and introduce a new method for structure analysis named ensemble difference distance matrix analysis (eDDM). The eDDM approach calculates and compares atomic distance matrices across large sets of homologous atomic structures to help identify the residue wise determinants underlying specific functional processes. An eDDM workflow is detailed along with an example application to a large protein family. As a new member of the Bio3D family, the Bio3D-eddm package supports both experimental and theoretical simulation-generated structures, is integrated with other methods for dissecting sequence-structure-function relationships, and can be used in a highly automated and reproducible manner. Bio3D is distributed as an integrated set of platform independent open source R packages available from: http://thegrantlab.org/bio3d/.

Structural dynamics of pentapeptide repeat proteins

Pentapeptide repeat proteins (PRPs) represent a large superfamily with more than 38 000 sequences in nearly 3500 species, the majority belonging to cyanobacteria but represented among all branches of life. PRPs contain at least eight consecutive pentapeptide repeats with the consensus (A/C/S/V/T/L/I)(D/N/S/K/E/I/R)(L/F)(S/T/R/E/Q/K/V/D)(G/D/E/N/R/Q/K). PRPs fold into right-handed quadrilateral β helices, also known as repeat-five-residue (Rfr)-folds, with four consecutive pentapeptide repeats comprising a single coil, the ~90° change in polypeptide direction in square-shaped coils achieved by type I, II and IV β turns, and hydrogen bonds between coils establishing β ladders on each Rfr-fold face. PRPs are broadly categorized into group 1 and 2 involved in antibiotic resistance and group 3 currently having unknown functions. Motivated by their intriguing structures, we are investigating PRP biophysical characteristics, including Rfr-fold thermal stability, β turn and β ladder hydrogen bond amide exchange rates and backbone dynamics. Here, we present analysis of 20 ns molecular dynamics (MD) simulations and all atom normal mode analysis (aaNMA) calculations for four group 1 and group 2 and four group 3 PRPs whose structures have been determined by X-ray crystallography. The MD cross-correlation matrices and aaNMA indicated strong correlated motion between adjacent coils and weak coupled motion between coils separated by one or more intervening coils. Slow anticorrelated motions were detected between adjacent coils in aaNMA modes that we hypothesize are requisite to access exchange-competent states necessary to permit solvent exchange of amide hydrogens involved in β-ladder and β-turns hydrogen bonds, which can have lifetimes on the order of months.

Mechanism of CcdA-Mediated Rejuvenation of DNA Gyrase

Most biological processes involve formation of transient complexes where binding of a ligand allosterically modulates function. The ccd toxin-antitoxin system is involved in plasmid maintenance and bacterial persistence. The CcdA antitoxin accelerates dissociation of CcdB from its complex with DNA gyrase, binds and neutralizes CcdB, but the mechanistic details are unclear. Using a series of experimental and computational approaches, we demonstrate the formation of transient ternary and quaternary CcdA:CcdB:gyrase complexes and delineate the molecular steps involved in the rejuvenation process. Binding of region 61-72 of CcdA to CcdB induces the vital structural and dynamic changes required to facilitate dissociation from gyrase, region 50-60 enhances the dissociation process through additional allosteric effects, and segment 37-49 prevents gyrase rebinding. This study provides insights into molecular mechanisms responsible for recovery of CcdB-poisoned cells from a persister-like state. Similar methodology can be used to characterize other important transient, macromolecular complexes.

How good are comparative models in the understanding of protein dynamics?

The 3D structure of a protein is essential to understand protein dynamics. If experimentally determined structure is unavailable, comparative models could be used to infer dynamics. However, the effectiveness of comparative models, compared to experimental structures, in inferring dynamics is not clear. To address this, we compared dynamics features of ~800 comparative models with their crystal structures using normal mode analysis. Average similarity in magnitude, direction, and correlation of residue motions is >0.8 (where value 1 is identical) indicating that the dynamics of models and crystal structures are highly similar. Accuracy of 3D structure and dynamics is significantly higher for models built on multiple and/or high sequence identity templates (>40%). Three-dimensional (3D) structure and residue fluctuations of models are closer to that of crystal structures than to templates (TM score 0.9 vs 0.7 and square inner product 0.92 vs 0.88). Furthermore, long-range molecular dynamics simulations on comparative models of RNase 1 and Angiogenin showed significant differences in the conformational sampling of conserved active-site residues that characterize differences in their activity levels. Similar analyses on two EGFR kinase variant models highlight the effect of mutations on the functional state-specific αC helix motions and these results corroborate with the previous experimental observations. Thus, our study adds confidence to the use of comparative models in understanding protein dynamics.

Hybrid Electron Microscopy Normal Mode Analysis with Scipion

Hybrid Electron Microscopy Normal Mode Analysis (HEMNMA) method was introduced in 2014. HEMNMA computes normal modes of a reference model (an atomic structure or an electron microscopy map) of a molecular complex and uses this model and its normal modes to analyze single-particle images of the complex to obtain information on its continuous conformational changes, by determining the full distribution of conformational variability from the images. An advantage of HEMNMA is a simultaneous determination of all parameters of each image (particle conformation, orientation, and shift) through their iterative optimization, which allows applications of HEMNMA even when the effects of conformational changes dominate those of orientational changes. HEMNMA was first implemented in Xmipp and was using MATLAB for statistical analysis of obtained conformational distributions and for fitting of underlying trajectories of conformational changes. A HEMNMA implementation independent of MATLAB is now available as part of a plugin of Scipion V2.0 (http://scipion.i2pc.es). This plugin, named ContinuousFlex, can be installed by following the instructions at https://pypi.org/project/scipion-em-continuousflex. In this article, we present this new HEMNMA software, which is user-friendly, totally free, and open-source. STATEMENT FOR A BROADER AUDIENCE: This article presents Hybrid Electron Microscopy Normal Mode Analysis (HEMNMA) software that allows analyzing single-particle images of a complex to obtain information on continuous conformational changes of the complex, by determining the full distribution of conformational variability from the images. The HEMNMA software is user-friendly, totally free, open-source, and available as part of ContinuousFlex plugin (https://pypi.org/project/scipion-em-continuousflex) of Scipion V2.0 (http://scipion.i2pc.es).

Binding mechanism of spinosine and venenatine molecules with p300 HAT enzyme: Molecular screening, molecular dynamics and free-energy analysis

The chromatin modification is regulated by the histone acetyltransferase (HAT) and histone deacetyltransferase (HDAC) enzymes; abnormal function of these enzymes leads to several malignant diseases. The inhibition of these enzymes using natural ligand molecules is an emerging technique to cure these diseases. The in vitro analysis of natural molecules, venenatine, spinosine, palmatine and taxodione are giving the best inhibition rate against p300 HAT enzyme. However, the detailed understanding of binding and the stability of these molecules with p300 HAT is not yet known. The aim of the present study is focused to determine the binding strength of the molecules from molecular dynamics simulation analysis. The docking analysis confirms that, the venenatine (-6.97 kcal/mol - conformer 8), spinosine (-6.52 kcal/mol conformer -10), palmatine (-5.72 kcal/mol conformer-3) and taxodione (-4.99 kcal/mol conformer-4) molecules form strong hydrogen bonding interactions with the key amino acid residues (Arg1410, Thr1411 and Trp1466) present in the active site of p300. In the molecular dynamics (MD) simulation, the spinosine retain these key interactions with the active site amino acid residues (Arg1410, Thr1411, and Trp1466) than venenatine and are stable throughout the simulation. The RMSD value of spinosine (0.5 to 1.3 Å) and venenatine (0.3 to 1.3 Å) are almost equal during the MD simulation. However, during the MD simulation, the intermolecular interaction between venenatine and the active site amino acid residues (Arg1410, Thr1411, and Trp1466) decreased on comparing with the spinosine-p300 interaction. The binding free energy of the spinosine (-15.30 kcal/mol) is relatively higher than the venenatine (-11.8 kcal/mol); this increment is attributed to the strong hydrogen bonding interactions of spinosine molecule with the active site amino acid residues of p300.

Geometrical Conversion of the EGFR Extracellular Domain by Adiabatic Mapping Combining Normal Mode Analysis of the Elastic Network Model and Energy Optimization

The activation of epidermal growth factor receptor (EGFR) involves the geometrical conversion of the extracellular domain (ECD) from the tethered to the extended forms with the dynamic rearrangement of the relative positions of four subdomains (SDs); however, this conversion process has not yet been thoroughly understood. We compare the two different forms of the X-ray crystal structures of ECD and simulate the ECD conversion process using adiabatic mapping that combines normal mode analysis of the elastic network model (ENM-NMA) and energy optimization. A comparison of the crystal structures reveals the rigidity of the intradomain geometry of the SD-I and -III backbone regardless of the form. The forward mapping from the tethered to the extended forms retains the intradomain geometry of the SD-I and -III backbone and reveals the trends to rearrange the relative positions of SD-I and -III and to dissociate the C-terminal tail of SD-IV from the hairpin loop in SD-II. The reverse mapping from the extended to the tethered forms complements the promotion of ECD conversion in the presence of epidermal growth factor (EGF).

Normal Mode Analysis as a Routine Part of a Structural Investigation

Normal mode analysis (NMA) is a technique that can be used to describe the flexible states accessible to a protein about an equilibrium position. These states have been shown repeatedly to have functional significance. NMA is probably the least computationally expensive method for studying the dynamics of macromolecules, and advances in computer technology and algorithms for calculating normal modes over the last 20 years have made it nearly trivial for all but the largest systems. Despite this, it is still uncommon for NMA to be used as a component of the analysis of a structural study. In this review, we will describe NMA, outline its advantages and limitations, explain what can and cannot be learned from it, and address some criticisms and concerns that have been voiced about it. We will then review the most commonly used techniques for reducing the computational cost of this method and identify the web services making use of these methods. We will illustrate several of their possible uses with recent examples from the literature. We conclude by recommending that NMA become one of the standard tools employed in any structural study.

RNA-Mediated Virus Assembly: Mechanisms and Consequences for Viral Evolution and Therapy

Viruses, entities composed of nucleic acids, proteins, and in some cases lipids lack the ability to replicate outside their target cells. Their components self-assemble at the nanoscale with exquisite precision-a key to their biological success in infection. Recent advances in structure determination and the development of biophysical tools such as single-molecule spectroscopy and noncovalent mass spectrometry allow unprecedented access to the detailed assembly mechanisms of simple virions. Coupling these techniques with mathematical modeling and bioinformatics has uncovered a previously unsuspected role for genomic RNA in regulating formation of viral capsids, revealing multiple, dispersed RNA sequence/structure motifs [packaging signals (PSs)] that bind cognate coat proteins cooperatively. The PS ensemble controls assembly efficiency and accounts for the packaging specificity seen in vivo. The precise modes of action of the PSs vary between viral families, but this common principle applies across many viral families, including major human pathogens. These insights open up the opportunity to block or repurpose PS function in assembly for both novel antiviral therapy and gene/drug/vaccine applications.

Closure of the Human TKFC Active Site: Comparison of the Apoenzyme and the Complexes Formed with Either Triokinase or FMN Cyclase Substrates

Human triokinase/flavin mononucleotide (FMN) cyclase (hTKFC) catalyzes the adenosine triphosphate (ATP)-dependent phosphorylation of D-glyceraldehyde and dihydroxyacetone (DHA), and the cyclizing splitting of flavin adenine dinucleotide (FAD). hTKFC structural models are dimers of identical subunits, each with two domains, K and L, with an L2-K1-K2-L1 arrangement. Two active sites lie between L2-K1 and K2-L1, where triose binds K and ATP binds L, although the resulting ATP-to-triose distance is too large (≈14 Å) for phosphoryl transfer. A 75-ns trajectory of molecular dynamics shows considerable, but transient, ATP-to-DHA approximations in the L2-K1 site (4.83 Å or 4.16 Å). To confirm the trend towards site closure, and its relationship to kinase activity, apo-hTKFC, hTKFC:2DHA:2ATP and hTKFC:2FAD models were submitted to normal mode analysis. The trajectory of hTKFC:2DHA:2ATP was extended up to 160 ns, and 120-ns trajectories of apo-hTKFC and hTKFC:2FAD were simulated. The three systems were comparatively analyzed for equal lengths (120 ns) following the principles of essential dynamics, and by estimating site closure by distance measurements. The full trajectory of hTKFC:2DHA:2ATP was searched for in-line orientations and short distances of DHA hydroxymethyl oxygens to ATP γ-phosphorus. Full site closure was reached only in hTKFC:2DHA:2ATP, where conformations compatible with an associative phosphoryl transfer occurred in L2-K1 for significant trajectory time fractions.

Investigation of activation mechanism and conformational stability of N-(4-chloro-3-trifluoromethyl-phenyl)-2-ethoxybenzamide and N-(4-chloro-3-trifluoromethyl-phenyl)-2-ethoxy-6-pentadecyl-benzamide in the: active site of p300 histone acetyl transferase enzyme by molecular dynamics and binding free energy studies

The CBP (CREB-binding protein) and p300 are related to transcriptional coactivator family and are involved in several post-translational modifications, in which the acetylation is an important factor because it commences the transcription process. Experimental studies report that CTPB (N-(4-chloro-3-trifluoromethyl-phenyl)-2-ethoxy-6-pentadecyl-benzamide) and CTB (N-(4-chloro-3-trifluoromethyl-phenyl)-2-ethoxybenzamide) are good activators of p300 HAT enzyme, but yet, the molecular mechanism of their activation is not explored. The present study pertains to determine the intermolecular interactions, stability and binding free energy of CTB and CTPB from the molecular docking, molecular dynamics (MD) simulation and binding free energy calculation. The docking studies of the molecules reveal that the docking score of CTPB (-15.64 kcal/mol) is higher than that of CTB (-12.30 kcal/mol); on the contrary, CTB forms a strong interaction with the key residues of catalytic site (Tyr1467 and Trp1436) compared with CTPB. The MD simulation shows the stability of both molecules in the active site of p300 and their interactions. Furthermore, both docking and MD simulation studies of CTB confirm that it forms expected key interactions and retain the interactions with the active site amino acid residues of p300 when compared with CTPB. For this reason, the CTB recruits more acetyl-CoA in the active site of p300 compared with CTPB; it leads to activate the acetylation process; hence, CTB may be a best activator than CTPB. The binding free energy value of CTPB (-24.79  ±  2.38 kcal/mol) is higher when compared with that of CTB (-12.14  ±  1.30 kcal/mol) molecule; perhaps, the interaction of pentadecyl chain of CTPB with p300, whereas in CTB, such a group is absent. Communicated by Ramaswamy H. Sarma.

Coarse-Grained Protein Dynamics Studies Using Elastic Network Models

Elastic networks have been used as simple models of proteins to study their slow structural dynamics. They consist of point-like particles connected by linear Hookean springs and hence are convenient for linear normal mode analysis around a given reference structure. Furthermore, dynamic simulations using these models can provide new insights. As the computational cost associated with these models is considerably lower compared to that of all-atom models, they are also convenient for comparative studies between multiple protein structures. In this review, we introduce examples of coarse-grained molecular dynamics studies using elastic network models and their derivatives, focusing on the nonlinear phenomena, and discuss their applicability to large-scale macromolecular assemblies.

Exploring molecular mechanism of allosteric inhibitor to relieve drug resistance of multiple mutations in HIV-1 protease by enhanced conformational sampling

Recently, allosteric regulations of HIV-1 protease (PR) are suggested as a promising approach to relieve drug resistance of mutations toward inhibitors targeting the active site of PR. Replica-exchange molecular dynamics (REMD) simulations and normal mode analysis (NMA) are integrated to enhance conformational sampling of PR. Molecular mechanics generalized Born surface area (MM-GBSA) method was applied to calculate binding free energies of three inhibitors APV, DRV, and NIT to the wild-type (WT) and multidrug resistance (MDR) PRs. The results suggest that binding free energies of APV and DRV are decreased in the MDR PR relative to the WT PR, suggesting drug resistance of mutations on these two inhibitors. However, the binding ability of the allosteric inhibitor NIT is not impaired in the MDR PR. In addition, internal dynamics analysis based on REMD simulations proves that mutations hardly produce obvious effect on the conformation of the MDR PR in comparison to the WT PR. Scanning of hydrophobic contacts and hydrogen bond contacts of inhibitors with residues of PRs on the concatenated trajectories of REMD demonstrates that mutations change the symmetric interaction networks of APV and DRV with PR, but do not generate obvious influence on the asymmetric interaction network of NIT with PR. In summary, allosteric inhibitor NIT can adapt the MDR PR better than those inhibitors toward the active site of PR, thus allosteric inhibitors of PR may be a possible channel to overcome drug resistance of PR.

Dynamical comparison between myoglobin and hemoglobin

Myoglobin and hemoglobin are globular hemeproteins, when the former is a monomer and the latter a heterotetramer. Despite the structural similarity of myoglobin to α and β subunits of hemoglobin, there is a functional difference between the two proteins, owing to the quaternary structure of hemoglobin. The effect of the quaternary structure of hemoglobin on the intrinsic dynamics of its subunits is explored by dynamical comparison of the two proteins. Anisotropic Network Model modes of motion were calculated for hemoglobin and myoglobin. Dynamical comparison between the proteins was performed using global and local Anisotropic Network Model mode alignment algorithms based on the algorithms of Smith-Waterman and Needleman-Wunsch for sequence comparison. The results indicate that the quaternary structure of hemoglobin substantially alters the intrinsic dynamics of its subunits, an effect that may contribute to the functional difference between the two proteins. Local dynamics similarity between the proteins is still observed at the major exit route of the ligand.

Fabrication and Characterization of Finite-Size DNA 2D Ring and 3D Buckyball Structures

In order to incorporate functionalization into synthesized DNA nanostructures, enhance their production yield, and utilize them in various applications, it is necessary to study their physical stabilities and dynamic characteristics. Although simulation-based analysis used for DNA nanostructures provides important clues to explain their self-assembly mechanism, structural function, and intrinsic dynamic characteristics, few studies have focused on the simulation of DNA supramolecular structures due to the structural complexity and high computational cost. Here, we demonstrated the feasibility of using normal mode analysis for relatively complex DNA structures with larger molecular weights, i.e., finite-size DNA 2D rings and 3D buckyball structures. The normal mode analysis was carried out using the mass-weighted chemical elastic network model (MWCENM) and the symmetry-constrained elastic network model (SCENM), both of which are precise and efficient modeling methodologies. MWCENM considers both the weight of the nucleotides and the chemical bonds between atoms, and SCENM can obtain mode shapes of a whole structure by using only a repeated unit and its connectivity with neighboring units. Our results show the intrinsic vibrational features of DNA ring structures, which experience inner/outer circle and bridge motions, as well as DNA buckyball structures having overall breathing and local breathing motions. These could be used as the fundamental basis for designing and constructing more complicated DNA nanostructures.

Heterodimer Binding Scaffolds Recognition via the Analysis of Kinetically Hot Residues

Physical interactions between proteins are often difficult to decipher. The aim of this paper is to present an algorithm that is designed to recognize binding patches and supporting structural scaffolds of interacting heterodimer proteins using the Gaussian Network Model (GNM). The recognition is based on the (self) adjustable identification of kinetically hot residues and their connection to possible binding scaffolds. The kinetically hot residues are residues with the lowest entropy, i.e., the highest contribution to the weighted sum of the fastest modes per chain extracted via GNM. The algorithm adjusts the number of fast modes in the GNM's weighted sum calculation using the ratio of predicted and expected numbers of target residues (contact and the neighboring first-layer residues). This approach produces very good results when applied to dimers with high protein sequence length ratios. The protocol's ability to recognize near native decoys was compared to the ability of the residue-level statistical potential of Lu and Skolnick using the Sternberg and Vakser decoy dimers sets. The statistical potential produced better overall results, but in a number of cases its predicting ability was comparable, or even inferior, to the prediction ability of the adjustable GNM approach. The results presented in this paper suggest that in heterodimers at least one protein has interacting scaffold determined by the immovable, kinetically hot residues. In many cases, interacting proteins (especially if being of noticeably different sizes) either behave as a rigid lock and key or, presumably, exhibit the opposite dynamic behavior. While the binding surface of one protein is rigid and stable, its partner's interacting scaffold is more flexible and adaptable.

Investigating the structural dynamics of the PIEZO1 channel activation and inactivation by coarse-grained modeling

The PIEZO channels, a family of mechanosensitive channels in vertebrates, feature a fast activation by mechanical stimuli (eg, membrane tension) followed by a slower inactivation. Although a medium-resolution structure of the trimeric form of PIEZO1 was solved by cryo-electron microscopy (cryo-EM), key structural changes responsible for the channel activation and inactivation are still unknown. Toward decrypting the structural mechanism of the PIEZO1 activation and inactivation, we performed systematic coarse-grained modeling using an elastic network model and related modeling/analysis tools (ie, normal mode analysis, flexibility and hotspot analysis, correlation analysis, and cryo-EM-based hybrid modeling and flexible fitting). We identified four key motional modes that may drive the tension-induced activation and inactivation, with fast and slow relaxation time, respectively. These modes allosterically couple the lateral and vertical motions of the peripheral domains to the opening and closing of the intra-cellular vestibule, enabling external mechanical forces to trigger, and regulate the activation/inactivation transitions. We also calculated domain-specific flexibility profiles, and predicted hotspot residues at key domain-domain interfaces and hinges. Our results offer unprecedented structural and dynamic information, which is consistent with the literature on mutational and functional studies of the PIEZO channels, and will guide future studies of this important family of mechanosensitive channels.

Structural analyses of the Haemophilus influenzae peptidoglycan synthase activator LpoA suggest multiple conformations in solution

In many Gram-negative bacteria, the peptidoglycan synthase PBP1A requires the outer membrane lipoprotein LpoA for constructing a functional peptidoglycan required for bacterial viability. Previously, we have shown that the C-terminal domain of Haemophilus influenzae LpoA (HiLpoA) has a highly conserved, putative substrate-binding cleft between two α/β lobes. Here, we report a 2.0 Å resolution crystal structure of the HiLpoA N-terminal domain. Two subdomains contain tetratricopeptide-like motifs that form a concave groove, but their relative orientation differs by ∼45° from that observed in an NMR structure of the Escherichia coli LpoA N domain. We also determined three 2.0-2.8 Å resolution crystal structures containing four independent full-length HiLpoA molecules. In contrast to an elongated model previously suggested for E. coli LpoA, each HiLpoA formed a U-shaped structure with a different C-domain orientation. This resulted from both N-domain twisting and rotation of the C domain (up to 30°) at the end of the relatively immobile interdomain linker. Moreover, a previously predicted hinge between the lobes of the LpoA C domain exhibited variations of up to 12°. Small-angle X-ray scattering data revealed excellent agreement with a model calculated by normal mode analysis from one of the full-length HiLpoA molecules but even better agreement with an ensemble of this molecule and two of the partially extended normal mode analysis-predicted models. The different LpoA structures helped explain how an outer membrane-anchored LpoA can either withdraw from or extend toward the inner membrane-bound PBP1A through peptidoglycan gaps and hence regulate the synthesis of peptidoglycan necessary for bacterial viability.

Dynamical differences of hemoglobin and the ionotropic glutamate receptor in different states revealed by a new dynamics alignment method

A new algorithm for comparison of protein dynamics is presented. Compared protein structures are superposed and their modes of motions are calculated using the anisotropic network model. The obtained modes are aligned using the dynamic programming algorithm of Needleman and Wunsch, commonly used for sequence alignment. Dynamical comparison of hemoglobin in the T and R2 states reveals that the dynamics of the allosteric effector 2,3-bisphosphoglycerate binding site is different in the two states. These differences can contribute to the selectivity of the effector to the T state. Similar comparison of the ionotropic glutamate receptor in the kainate+(R,R)-2b and ZK bound states reveals that the kainate+(R,R)-2b bound states slow modes describe upward motions of ligand binding domain and the transmembrane domain regions. Such motions may lead to the opening of the receptor. The upper lobes of the LBDs of the ZK bound state have a smaller interface with the amino terminal domains above them and have a better ability to move together. The present study exemplifies the use of dynamics comparison as a tool to study protein function. Proteins 2017; 85:1507-1517. © 2014 Wiley Periodicals, Inc.

Dynamic analysis of the human brain with complex cerebral sulci

The brain is one of the most vulnerable organs inside the human body. Head accidents often appear in daily life and are easy to cause different level of brain damage inside the skull. Once the brain suffered intense locomotive impact, external injuries, falls, or other accidents, it will result in different degrees of concussion. This study employs finite element analysis to compare the dynamic characteristics between the geometric models of an assumed simple brain tissue and a brain tissue with complex cerebral sulci. It is aimed to understand the free vibration of the internal brain tissue and then to protect the brain from injury caused by external influences. Reverse engineering method is used for a Classic 5-Part Brain (C18) model produced by 3B Scientific Corporation. 3D optical scanner is employed to scan the human brain structure model with complex cerebral sulci and imported into 3D graphics software to construct a solid brain model to simulate the real complex brain tissue. Obtaining the normal mode analysis by inputting the material properties of the true human brain into finite element analysis software, and then to compare the simplified and the complex of brain models.

Probing the structural dynamics of the CRISPR-Cas9 RNA-guided DNA-cleavage system by coarse-grained modeling

In the adaptive immune systems of many bacteria and archaea, the Cas9 endonuclease forms a complex with specific guide/scaffold RNA to identify and cleave complementary target sequences in foreign DNA. This DNA targeting machinery has been exploited in numerous applications of genome editing and transcription control. However, the molecular mechanism of the Cas9 system is still obscure. Recently, high-resolution structures have been solved for Cas9 in different structural forms (e.g., unbound forms, RNA-bound binary complexes, and RNA-DNA-bound tertiary complexes, corresponding to an inactive state, a pre-target-bound state, and a cleavage-competent or product state), which offered key structural insights to the Cas9 mechanism. To further probe the structural dynamics of Cas9 interacting with RNA and DNA at the amino-acid level of details, we have performed systematic coarse-grained modeling using an elastic network model and related analyses. Our normal mode analysis predicted a few key modes of collective motions that capture the observed conformational changes featuring large domain motions triggered by binding of RNA and DNA. Our flexibility analysis identified specific regions with high or low flexibility that coincide with key functional sites (such as DNA/RNA-binding sites, nuclease cleavage sites, and key hinges). We also identified a small set of hotspot residues that control the energetics of functional motions, which overlap with known functional sites and offer promising targets for future mutagenesis efforts to improve the specificity of Cas9. Finally, we modeled the conformational transitions of Cas9 from the unbound form to the binary complex and then the tertiary complex, and predicted a distinct sequence of domain motions. In sum, our findings have offered rich structural and dynamic details relevant to the Cas9 machinery, and will guide future investigation and engineering of the Cas9 systems. Proteins 2017; 85:342-353. © 2016 Wiley Periodicals, Inc.