Building Quantitative Bridges between Dynamics and Sequences of SARS-CoV-2 Main Protease and a Diverse Set of Thirty-Two Proteins.

Proteases are major drug targets for many viral diseases. However, mutations can render several antiprotease drugs inefficient rapidly even though these mutations may not alter protein structures significantly. Understanding relations between quickly mutating residues, protease structures, and the dynamics of the proteases is crucial for designing potent drugs. Due to this reason, we studied relations between the evolutionary information on residues in the amino acid sequences and protein dynamics for SARS-CoV-2 main protease. More precisely, we analyzed three dynamical quantities (Schlitter entropy, root-mean-square fluctuations, and dynamical flexibility index) and their relation to the amino acid conservation extracted from multiple sequence alignments of the main protease. We showed that a quantifiable similarity can be built between a sequence-based quantity called Jensen-Shannon conservation and those three dynamical quantities. We validated this similarity for a diverse set of 32 different proteins, other than the SARS-CoV-2 main protease. We believe that establishing these kinds of quantitative bridges will have larger implications for all viral proteases as well as all proteins.

Impact of dimerization and N3 binding on molecular dynamics of SARS-CoV and SARS-CoV-2 main proteases.

SARS-CoV-2 main protease is one of the major targets in drug development efforts against Covid-19. Even though several structures were reported to date, its dynamics is not understood well. In particular, impact of dimerization and ligand binding on the dynamics is an important issue to investigate. In this study, we performed molecular dynamics simulations of SARS-CoV and SARS-CoV-2 main proteases to investigate influence of dimerization on the dynamics by modeling monomeric and dimeric apo and holo forms. The dimerization causes an organization of the interdomain dynamics as well as some local structural changes. Moreover, we investigated impact of a peptide mimetic (N3) on the dynamics of SARS-CoV and SARS-CoV-2 Mpro. The ligand binding to the dimeric forms causes some key local changes at the dimer interface and it causes an allosteric interaction between the active sites of two protomers. Our results support the idea that only one protomer is active on SARS-CoV-2 due to this allosteric interaction. Additionally, we analyzed the molecular dynamics trajectories from graph theoretical perspective and found that the most influential residues - as measured by eigenvector centrality - are a group of residues in active site and dimeric interface of the protease. This study may form a bridge between what we know about the dynamics of SARS-CoV and SARS-CoV-2 Mpro. We think that enlightening allosteric communication of the active sites and the role of dimerization in SARS-CoV-2 Mpro can contribute to development of novel drugs against this global health problem as well as other similar proteases. Communicated by Ramaswamy H. Sarma.

Extracting Dynamical Correlations and Identifying Key Residues for Allosteric Communication in Proteins by correlationplus.

Extracting dynamical pairwise correlations and identifying key residues from large molecular dynamics trajectories or normal-mode analysis of coarse-grained models are important for explaining various processes like ligand binding, mutational effects, and long-distance interactions. Efficient and flexible tools to perform this task can provide new insights about residues involved in allosteric regulation and protein function. In addition, combining and comparing dynamical coupling information with sequence coevolution data can help to understand better protein function. To this aim, we developed a Python package called correlationplus to calculate, visualize, and analyze pairwise correlations. In this way, the package aids to identify key residues and interactions in proteins. The source code of correlationplus is available under LGPL version 3 at https://github.com/tekpinar/correlationplus. The current version of the package (0.2.0) can be installed with common installation methods like conda or pip in addition to source code installation. Moreover, docker images are also available for usage of the code without installation.

Competing Roles of Ca2+ and Nonmuscle Myosin IIA on the Dynamics of the Metastasis-Associated Protein S100A4.

The calcium-binding protein S100A4 plays an important role in a wide range of biological processes such as cell motility, invasion, angiogenesis, survival, differentiation, contractility, and tumor metastasis and interacts with a range of partners. To understand the functional roles and interplay of S100A4 binding partners such as Ca2+ and nonmuscle myosin IIA (NMIIA), we used molecular dynamics simulations to investigate apo S100A4 and four holo S100A4 structures: S100A4 bound to Ca2+, S100A4 bound to NMIIA, S100A4 bound to Ca2+ and NMIIA, and a mutated S100A4 bound to Ca2+ and NMIIA. Our results show that two competing factors, namely, Ca2+-induced activation and NMIIA-induced inhibition, modulate the dynamics of S100A4 in a competitive manner. Moreover, Ca2+ binding results in enhanced dynamics, regulating the interactions of S100A4 with NMIIA, while NMIIA induces asymmetric dynamics between the chains of S100A4. The results also show that in the absence of Ca2+ the S100A4-NMIIA interaction is weak compared to that of between S100A4 bound to Ca2+ and NMIIA, which may offer a quick response to dropping calcium levels. In addition, certain mutations are shown to play a marked role on the dynamics of S100A4. The results described here contribute to understanding the interactions of S100A4 with NMIIA and the functional roles of Ca2+, NMIIA, and certain mutations on the dynamics of S100A4. The results of this study could be interesting for the development of inhibitors that exploit the shift of balance between the competing roles of Ca2+ and NMIIA.

How cyanophage S-2L rejects adenine and incorporates 2-aminoadenine to saturate hydrogen bonding in its DNA.

Bacteriophages have long been known to use modified bases in their DNA to prevent cleavage by the host's restriction endonucleases. Among them, cyanophage S-2L is unique because its genome has all its adenines (A) systematically replaced by 2-aminoadenines (Z). Here, we identify a member of the PrimPol family as the sole possible polymerase of S-2L and we find it can incorporate both A and Z in front of a T. Its crystal structure at 1.5 Å resolution confirms that there is no structural element in the active site that could lead to the rejection of A in front of T. To resolve this contradiction, we show that a nearby gene is a triphosphohydolase specific of dATP (DatZ), that leaves intact all other dNTPs, including dZTP. This explains the absence of A in S-2L genome. Crystal structures of DatZ with various ligands, including one at sub-angstrom resolution, allow to describe its mechanism as a typical two-metal-ion mechanism and to set the stage for its engineering.

Structural Studies of HNA Substrate Specificity in Mutants of an Archaeal DNA Polymerase Obtained by Directed Evolution.

Archaeal DNA polymerases from the B-family (polB) have found essential applications in biotechnology. In addition, some of their variants can accept a wide range of modified nucleotides or xenobiotic nucleotides, such as 1,5-anhydrohexitol nucleic acid (HNA), which has the unique ability to selectively cross-pair with DNA and RNA. This capacity is essential to allow the transmission of information between different chemistries of nucleic acid molecules. Variants of the archaeal polymerase from Thermococcus gorgonarius, TgoT, that can either generate HNA from DNA (TgoT_6G12) or DNA from HNA (TgoT_RT521) have been previously identified. To understand how DNA and HNA are recognized and selected by these two laboratory-evolved polymerases, we report six X-ray structures of these variants, as well as an in silico model of a ternary complex with HNA. Structural comparisons of the apo form of TgoT_6G12 together with its binary and ternary complexes with a DNA duplex highlight an ensemble of interactions and conformational changes required to promote DNA or HNA synthesis. MD simulations of the ternary complex suggest that the HNA-DNA hybrid duplex remains stable in the A-DNA helical form and help explain the presence of mutations in regions that would normally not be in contact with the DNA if it were not in the A-helical form. One complex with two incorporated HNA nucleotides is surprisingly found in a one nucleotide-backtracked form, which is new for a DNA polymerase. This information can be used for engineering a new generation of more efficient HNA polymerase variants.

Structural evidence for an in trans base selection mechanism involving Loop1 in polymerase µ at an NHEJ double-strand break junction.

Eukaryotic DNA polymerase (Pol) X family members such as Pol µ and terminal deoxynucleotidyl transferase (TdT) are important components for the nonhomologous DNA end-joining (NHEJ) pathway. TdT participates in a specialized version of NHEJ, V(D)J recombination. It has primarily nontemplated polymerase activity but can take instructions across strands from the downstream dsDNA, and both activities are highly dependent on a structural element called Loop1. However, it is unclear whether Pol µ follows the same mechanism, because the structure of its Loop1 is disordered in available structures. Here, we used a chimeric TdT harboring Loop1 of Pol µ that recapitulated the functional properties of Pol µ in ligation experiments. We solved three crystal structures of this TdT chimera bound to several DNA substrates at 1.96-2.55 Å resolutions, including a full DNA double-strand break (DSB) synapsis. We then modeled the full Pol µ sequence in the context of one these complexes. The atomic structure of an NHEJ junction with a Pol X construct that mimics Pol µ in a reconstituted system explained the distinctive properties of Pol µ compared with TdT. The structure suggested a mechanism of base selection relying on Loop1 and taking instructions via the in trans templating base independently of the primer strand. We conclude that our atomic-level structural observations represent a paradigm shift for the mechanism of base selection in the Pol X family of DNA polymerases.

Only a Subset of Normal Modes is Sufficient to Identify Linear Correlations in Proteins.

Identification of correlated residues in proteins is very important for many areas of protein research such as drug design, protein domain classification, signal transmission, allostery and mutational studies. Pairwise residue correlations in proteins can be obtained from experimental and theoretical ensembles. Since it is difficult to obtain proteins in various conformational states experimentally, theoretical methods such as all-atom molecular dynamics simulations and normal-mode analysis are commonly used methods to obtain protein ensembles and, therefore, pairwise residue correlations. The extent of agreement for the correlations obtained with all-atom molecular dynamics and elastic network model based normal-mode analysis is an important issue to investigate due to orders of magnitude computational advantage in terms of wall time for normal-mode based calculation. We performed multiple microsecond long equilibrium classical molecular dynamics simulations for six proteins. We calculated normalized dynamical cross-correlations and linear mutual information as pairwise residue correlations from the trajectories of these simulations. Then, we calculated the same pairwise residue correlations with two elastic network model based normal-mode analysis methods and compared our results with the former. The results show that elastic network model based normal-mode analysis can provide a fast and accurate estimation of linear correlations within proteins. Finally, we observed that only a subset of modes is sufficient to obtain linear correlations in proteins. This conclusion has crucial implications for understanding correlations within very large protein assemblies such as viral capsids.

Molecular dynamics study of the effect of active site protonation on Helicobacter pylori 5'-methylthioadenosine/S-adenosylhomocysteine nucleosidase.

The protein 5'-methylthioadenosine/S-adenosylhomocysteine nucleosidase (MTAN) is involved in the quorum sensing of several bacterial species, including Helicobacter pylori. In particular, these bacteria depend on MTAN for synthesis of vitamin K2 homologs. The residue D198 in the active site of MTAN seems to be of crucial importance, by acting as a hydrogen-bond acceptor for the ligand. In this study, we investigated the conformation and dynamics of apo and holo H. pylori MTAN (HpMTAN), and assessed the effect of protonation of D198 by use of molecular dynamics simulations. Our results show that protonation of the active site of HpMTAN can cause a conformational transition from a closed state to an open state even in the absence of substrate, via inter-chain mechanical coupling.

Opening mechanism of adenylate kinase can vary according to selected molecular dynamics force field.

Adenylate kinase is a widely used test case for many conformational transition studies. It performs a large conformational transition between closed and open conformations while performing its catalytic function. To understand conformational transition mechanism and impact of force field choice on E. Coli adenylate kinase, we performed all-atom explicit solvent classical molecular dynamics simulations starting from the closed conformation with four commonly used force fields, namely, Amber99, Charmm27, Gromos53a6, Opls-aa. We carried out 40 simulations, each one 200 ns. We analyzed completely 12 of them that show full conformational transition from the closed state to the open one. Our study shows that different force fields can have a bias toward different transition pathways. Transition time scales, frequency of conformational transitions, order of domain motions and free energy landscapes of each force field may also vary. In general, Amber99 and Charmm27 behave similarly while Gromos53a6 results have a resemblance to the Opls-aa force field results.

High-resolution modeling of protein structures based on flexible fitting of low-resolution structural data.

To circumvent the difficulty of directly solving high-resolution biomolecular structures, low-resolution structural data from Cryo-electron microscopy (EM) and small angle solution X-ray scattering (SAXS) are increasingly used to explore multiple conformational states of biomolecular assemblies. One promising venue to obtain high-resolution structural models from low-resolution data is via data-constrained flexible fitting. To this end, we have developed a new method based on a coarse-grained Cα-only protein representation, and a modified form of the elastic network model (ENM) that allows large-scale conformational changes while maintaining the integrity of local structures including pseudo-bonds and secondary structures. Our method minimizes a pseudo-energy which linearly combines various terms of the modified ENM energy with an EM/SAXS-fitting score and a collision energy that penalizes steric collisions. Unlike some previous flexible fitting efforts using the lowest few normal modes, our method effectively utilizes all normal modes so that both global and local structural changes can be fully modeled with accuracy. This method is also highly efficient in computing time. We have demonstrated our method using adenylate kinase as a test case which undergoes a large open-to-close conformational change. The EM-fitting method is available at a web server (http://enm.lobos.nih.gov), and the SAXS-fitting method is available as a pre-compiled executable upon request.

Unzipping of neuronal snare protein with steered molecular dynamics occurs in three steps.

Soluble NSF-attachment protein receptors (SNAREs) play a crucial role in membrane fusion. Neuronal SNAREs, a four-helix bundle, help synaptic vesicles fuse with plasma membranes. We applied constant velocity pulling forces in silico to C terminal of synaptobrevin, one of the helices in the bundle, to understand unzipping mechanism of neuronal SNAREs. We observed unzipping of snaptobrevin from the other helices in three steps: linker domain unzipping, C terminal unzipping and N terminal unzipping. Our results have good qualitative agreement with a recent optical tweezer experiment that observes this stepwise unzipping. Since we performed 14 different simulations for two large spring force constants, our results are robust and they reveal atomistic details of these distinct unzipping steps.

Molecular dynamics investigation of Helicobacter pylori chemotactic protein CheY1 and two mutants.

CheY is a chemotactic response regulator protein modulating the rotation direction of bacterial flagellar motors. It plays an important role in the colonization and infection of Helicobacter pylori (H. pylori), which is a common pathogen. Recently, the structure of CheY1 of H. pylori (HpCheY1) was solved, showing similarities and differences with CheY from E. coli. Here, we report 200 ns atomistic molecular dynamics (MD) simulations of HpCheY1 and two mutants. The results suggest that the surface of HpCheY1 has regions with increased affinity for Mg²âº. In addition, wildtype HpCheY1 (WT HpCheY1) shows characteristic dynamics in helix 4, which is involved in FliM binding. This dynamics is altered in the D53A mutant and completely suppressed in the T84A mutant. The results are discussed in relation to the binding and function of HpCheY1.

Analysis of protein conformational transitions using elastic network model.

In this chapter, we demonstrate the usage of a coarse-grained elastic network model to analyze protein conformational transitions in the NS3 helicase (NS3hel) of Hepatitis C virus (HCV). This analysis allows us to identify and visualize collective domain motions involved in the conformational transitions and predict the order of structural events during the transitions. It is highly efficient and applicable to many multi-domain protein structures which undergo large conformational changes to fulfill their functions. This method is made available through a Web server ( http://enm.lobos.nih.gov ).

Coarse-grained and all-atom modeling of structural states and transitions in hemoglobin.

Hemoglobin (Hb), an oxygen-binding protein composed of four subunits (α1, α2, ß1, and ß2), is a well-known example of allosteric proteins that are capable of cooperative ligand binding. Despite decades of studies, the structural basis of its cooperativity remains controversial. In this study, we have integrated coarse-grained (CG) modeling, all-atom simulation, and structural data from X-ray crystallography and wide-angle X-ray scattering (WAXS), aiming to probe dynamic properties of the two structural states of Hb (T and R state) and the transitions between them. First, by analyzing the WAXS data of unliganded and liganded Hb, we have found that the structural ensemble of T or R state is dominated by one crystal structure of Hb with small contributions from other crystal structures of Hb. Second, we have used normal mode analysis to identify two distinct quaternary rotations between the α1ß1 and α2ß2 dimer, which drive the transitions between T and R state. We have also identified the hot-spot residues whose mutations are predicted to greatly change these quaternary motions. Third, we have generated a CG transition pathway between T and R state, which predicts a clear order of quaternary and tertiary changes involving α and ß subunits in Hb. Fourth, we have used the accelerated molecular dynamics to perform an all-atom simulation starting from the T state of Hb, and we have observed a transition toward the R state of Hb. Further analysis of crystal structural data and the all-atom simulation trajectory has corroborated the order of quaternary and tertiary changes predicted by CG modeling.

Structure-based simulations of the translocation mechanism of the hepatitis C virus NS3 helicase along single-stranded nucleic acid.

The NS3 helicase of Hepatitis C virus is an ATP-fueled molecular motor that can translocate along single-stranded (ss) nucleic acid, and unwind double-stranded nucleic acids. It makes a promising antiviral target and an important prototype system for helicase research. Despite recent progress, the detailed mechanism of NS3 helicase remains unknown. In this study, we have combined coarse-grained (CG) and atomistic simulations to probe the translocation mechanism of NS3 helicase along ssDNA. At the residue level of detail, our CG simulations have captured functionally important interdomain motions of NS3 helicase and reproduced single-base translocation of NS3 helicase along ssDNA in the 3'-5' direction, which is in good agreement with experimental data and the inchworm model. By combining the CG simulations with residue-specific perturbations to protein-DNA interactions, we have identified a number of key residues important to the translocation machinery that agree with previous structural and mutational studies. Additionally, our atomistic simulations with targeted molecular dynamics have corroborated the findings of CG simulations and further revealed key protein-DNA hydrogen bonds that break/form during the transitions. This study offers, to our knowledge, the most detailed and realistic simulations of translocation mechanism of NS3 helicase. The simulation protocol established in this study will be useful for designing inhibitors that target the translocation machinery of NS3 helicase, and for simulations of a variety of nucleic-acid-based molecular motors.

Accurate flexible fitting of high-resolution protein structures to small-angle x-ray scattering data using a coarse-grained model with implicit hydration shell.

Small-angle x-ray scattering (SAXS) is a powerful technique widely used to explore conformational states and transitions of biomolecular assemblies in solution. For accurate model reconstruction from SAXS data, one promising approach is to flexibly fit a known high-resolution protein structure to low-resolution SAXS data by computer simulations. This is a highly challenging task due to low information content in SAXS data. To meet this challenge, we have developed what we believe to be a novel method based on a coarse-grained (one-bead-per-residue) protein representation and a modified form of the elastic network model that allows large-scale conformational changes while maintaining pseudobonds and secondary structures. Our method optimizes a pseudoenergy that combines the modified elastic-network model energy with a SAXS-fitting score and a collision energy that penalizes steric collisions. Our method uses what we consider a new implicit hydration shell model that accounts for the contribution of hydration shell to SAXS data accurately without explicitly adding waters to the system. We have rigorously validated our method using five test cases with simulated SAXS data and three test cases with experimental SAXS data. Our method has successfully generated high-quality structural models with root mean-squared deviation of 1 âˆ¼ 3 Å from the target structures.

Predicting order of conformational changes during protein conformational transitions using an interpolated elastic network model.

The decryption of sequence of structural events during protein conformational transitions is essential to a detailed understanding of molecular functions of various biological nanomachines. Coarse-grained models have proven useful by allowing highly efficient simulations of protein conformational dynamics. By combining two coarse-grained elastic network models constructed based on the beginning and end conformations of a transition, we have developed an interpolated elastic network model to generate a transition pathway between the two protein conformations. For validation, we have predicted the order of local and global conformational changes during key ATP-driven transitions in three important biological nanomachines (myosin, F(1) ATPase and chaperonin GroEL). We have found that the local conformational change associated with the closing of active site precedes the global conformational change leading to mechanical motions. Our finding is in good agreement with the distribution of intermediate experimental structures, and it supports the importance of local motions at active site to drive or gate various conformational transitions underlying the workings of a diverse range of biological nanomachines.

Large-scale evaluation of dynamically important residues in proteins predicted by the perturbation analysis of a coarse-grained elastic model.

BACKGROUND: It is increasingly recognized that protein functions often require intricate conformational dynamics, which involves a network of key amino acid residues that couple spatially separated functional sites. Tremendous efforts have been made to identify these key residues by experimental and computational means. RESULTS: We have performed a large-scale evaluation of the predictions of dynamically important residues by a variety of computational protocols including three based on the perturbation and correlation analysis of a coarse-grained elastic model. This study is performed for two lists of test cases with >500 pairs of protein structures. The dynamically important residues predicted by the perturbation and correlation analysis are found to be strongly or moderately conserved in >67% of test cases. They form a sparse network of residues which are clustered both in 3D space and along protein sequence. Their overall conservation is attributed to their dynamic role rather than ligand binding or high network connectivity. CONCLUSION: By modeling how the protein structural fluctuations respond to residue-position-specific perturbations, our highly efficient perturbation and correlation analysis can be used to dissect the functional conformational changes in various proteins with a residue level of detail. The predictions of dynamically important residues serve as promising targets for mutational and functional studies.