Integrating protein structural dynamics and evolutionary analysis with Bio3D

In-Silico analysis reveals lower transcription efficiency of C241T variant of SARS-CoV-2 with host replication factors MADP1 and hnRNP-1

Novel severe acute respiratory syndrome-coronavirus-2 (SARS-CoV-2) has claimed more than 3.3 million lives worldwide and still counting. As per the GISAID database, the genomics of SARS-CoV-2 has been extensively studied, with more than 500 genome submissions per day. Out of several hotspot mutations within the SARS-CoV-2 genome, recent research has focused mainly on the missense variants. Moreover, significantly less attention has been accorded to delineate the role of the untranslated regions (UTRs) of the SARS-CoV-2 genome in the disease progression and etiology. One of the most frequent 5' UTR variants in the SARS-CoV-2 genome is the C241T, with a global frequency of more than 95 %. In the present study, the effect of the C241T mutation has been studied with respect to the changes in RNA structure and its interaction with the host replication factors MADP1 Zinc finger CCHC-type and RNA-binding motif 1 (hnRNP1). The results obtained from molecular docking and molecular dynamics simulation indicated weaker interaction of C241T mutant stem-loops with the host transcription factor MADP1, indicating a reduced replication efficiency. The results are also correlated with increased recovery rates and decreased death rates of global SARS-CoV-2 cases.

Helical reconstruction of Salmonella and Shigella needle filaments attached to type 3 basal bodies

Gram-negative pathogens evolved a syringe-like nanomachine, termed type 3 secretion system, to deliver protein effectors into the cytoplasm of host cells. An essential component of this system is a long helical needle filament that protrudes from the bacterial surface and connects the cytoplasms of the bacterium and the eukaryotic cell. Previous structural research was predominantly focused on reconstituted type 3 needle filaments, which lacked the biological context. In this work we introduce a facile procedure to obtain high-resolution cryo-EM structure of needle filaments attached to the basal body of type 3 secretion systems. We validate our approach by solving the structure of Salmonella PrgI filament and demonstrate its utility by obtaining the first high-resolution cryo-EM reconstruction of Shigella MxiH filament. Our work paves the way to systematic structural characterization of attached type 3 needle filaments in the context of mutagenesis studies, protein structural evolution and drug development.

Application Fields, Positions, and Bioinformatic Mining of Non-active Sites: A Mini-Review

Active sites of enzymes play a vital role in catalysis, and researchhas been focused on the interactions between active sites and substrates to understand the biocatalytic process. However, the active sites distal to the catalytic cavity also participate in catalysis by maintaining the catalytic conformations. Therefore, some researchers have begun to investigate the roles of non-active sites in proteins, especially for enzyme families with different functions. In this mini-review, we focused on recent progress in research on non-active sites of enzymes. First, we outlined two major research methodswith non-active sites as direct targets, including understanding enzymatic mechanisms and enzyme engineering. Second, we classified the positions of reported non-active sites in enzyme structures and studied the molecular mechanisms underlying their functions, according to the literature on non-active sites. Finally, we summarized the results of bioinformatic analysisof mining non-active sites as targets for protein engineering.

The N-terminal Helix-Turn-Helix Motif of Transcription Factors MarA and Rob Drives DNA Recognition

DNA-binding proteins play an important role in gene regulation and cellular function. The transcription factors MarA and Rob are two homologous members of the AraC/XylS family that regulate multidrug resistance. They share a common DNA-binding domain, and Rob possesses an additional C-terminal domain that permits binding of low-molecular weight effectors. Both proteins possess two helix-turn-helix (HTH) motifs capable of binding DNA; however, while MarA interacts with its promoter through both HTH-motifs, prior studies indicate that Rob binding to DNA via a single HTH-motif is sufficient for tight binding. In the present work, we perform microsecond time scale all-atom simulations of the binding of both transcription factors to different DNA sequences to understand the determinants of DNA recognition and binding. Our simulations characterize sequence-dependent changes in dynamical behavior upon DNA binding, showcasing the role of Arg40 of the N-terminal HTH-motif in allowing for specific tight binding. Finally, our simulations demonstrate that an acidic C-terminal loop of Rob can control the DNA binding mode, facilitating interconversion between the distinct DNA binding modes observed in MarA and Rob. In doing so, we provide detailed molecular insight into DNA binding and recognition by these proteins, which in turn is an important step toward the efficient design of antivirulence agents that target these proteins.

Structure and Sequence-based Computational Approaches to Allosteric Signal Transduction: Application to Electromechanical Coupling in Voltage-gated Ion Channels

Allosteric signaling underlies the function of many biomolecules, including membrane proteins such as ion channels. Experimental methods have enabled specific quantitative insights into the coupling between the voltage sensing domain (VSD) and the pore gate of voltage-gated ion channels, located tens of Ångström apart from one another, as well as pinpointed specific residues and domains that participate in electromechanical signal transmission. Nevertheless, an overall atomic-level resolution picture is difficult to obtain from these methods alone. Today, thanks to the cryo-EM resolution revolution, we have access to high resolution structures of many different voltage-gated ion channels in various conformational states, putting a quantitative description of the processes at the basis of these changes within our close reach. Here, we review computational methods that build on structures to detect and characterize allosteric signaling and pathways. We then examine what has been learned so far about electromechanical coupling between VSD and pore using such methods. While no general theory of electromechanical coupling in voltage-gated ion channels integrating results from all these methods is available yet, we outline the types of insights that could be achieved in the near future using the methods that have not yet been put to use in this field of application.

Computational-Driven Epitope Verification and Affinity Maturation of TLR4-Targeting Antibodies

Toll-like receptor (TLR) signaling plays a critical role in the induction and progression of autoimmune diseases such as rheumatoid arthritis, systemic lupus erythematous, experimental autoimmune encephalitis, type 1 diabetes mellitus and neurodegenerative diseases. Deciphering antigen recognition by antibodies provides insights and defines the mechanism of action into the progression of immune responses. Multiple strategies, including phage display and hybridoma technologies, have been used to enhance the affinity of antibodies for their respective epitopes. Here, we investigate the TLR4 antibody-binding epitope by computational-driven approach. We demonstrate that three important residues, i.e., Y328, N329, and K349 of TLR4 antibody binding epitope identified upon in silico mutagenesis, affect not only the interaction and binding affinity of antibody but also influence the structural integrity of TLR4. Furthermore, we predict a novel epitope at the TLR4-MD2 interface which can be targeted and explored for therapeutic antibodies and small molecules. This technique provides an in-depth insight into antibody-antigen interactions at the resolution and will be beneficial for the development of new monoclonal antibodies. Computational techniques, if coupled with experimental methods, will shorten the duration of rational design and development of antibody therapeutics.

Association of sigma-1 receptor with dopamine transporter attenuates the binding of methamphetamine via distinct helix-helix interactions

Dopamine transporter (DAT) and sigma-1 receptor (σ1R) are potential therapeutic targets to reduce the psychostimulant effects induced by methamphetamine (METH). Interaction of σ1R with DAT could modulate the binding of METH, but the molecular basis of the association of the two transmembrane proteins and how their interactions mediate the binding of METH to DAT or σ1R remain unclear. Here, we characterize the protein-ligand and protein-protein interactions at a molecular level by various theoretical approaches. The present results show that METH adopts a different binding pose in the binding pocket of σ1R and is more likely to act as an agonist. The relatively lower binding affinity of METH to σ1R supports the role of antagonists as inhibitors that protect against METH-induced effects. We demonstrate that σ1R could bind to Drosophila melanogaster DAT (dDAT) through interactions with either the transmembrane helix α12 or α5 of dDAT. Our results showed that the truncated σ1R displays stronger association with dDAT than the full-length σ1R. Although different helix-helix interactions between σ1R and dDAT lead to distinct effects on the dynamics of individual protein, both associations attenuate the binding affinity of METH to dDAT, particularly in the interactions with the helix α5 of dDAT. Together, the present study provides the first computational investigation on the molecular mechanism of coupling METH binding and the association of σ1R with dDAT.

Mapping the Intramolecular Communications among Different Glutamate Dehydrogenase States Using Molecular Dynamics

Glutamate dehydrogenase (GDH) is a ubiquitous enzyme that catalyzes the reversible oxidative deamination of glutamate to α-ketoglutarate. It acts as an important branch-point enzyme between carbon and nitrogen metabolisms. Due to the multifaceted roles of GDH in cancer, hyperinsulinism/hyperammonemia, and central nervous system development and pathologies, tight control of its activity is necessitated. To date, several GDH structures have been solved in its closed form; however, intrinsic structural information in its open and apo forms are still deficient. Moreover, the allosteric communications and conformational changes taking place in the three different GDH states are not well studied. To mitigate these drawbacks, we applied unbiased molecular dynamic simulations (MD) and network analysis to three different GDH states i.e., apo, active, and inactive forms, for investigating their modulatory mechanisms. In this paper, based on MD and network analysis, crucial residues important for signal transduction, conformational changes, and maps of information flow among the different GDH states were elucidated. Moreover, with the recent findings of allosteric modulators, an allosteric wiring illustration of GDH intramolecular signal transductions would be of paramount importance to obtain the process of this enzyme regulation. The structural insights gained from this study will pave way for large-scale screening of GDH regulators and could support researchers in the design and development of new and potent GDH ligands.

Structure and Dynamics of Meprin β in Complex with a Hydroxamate-Based Inhibitor

The astacin protease Meprin β represents an emerging target for drug development due to its potential involvement in disorders such as acute and chronic kidney injury and fibrosis. Here, we elaborate on the structural basis of inhibition by a specific Meprin β inhibitor. Our analysis of the crystal structure suggests different binding modes of the inhibitor to the active site. This flexibility is caused, at least in part, by movement of the C-terminal region of the protease domain (CTD). The CTD movement narrows the active site cleft upon inhibitor binding. Compared with other astacin proteases, among these the highly homologous isoenzyme Meprin α, differences in the subsites account for the unique selectivity of the inhibitor. Although the inhibitor shows substantial flexibility in orientation within the active site, the structural data as well as binding analyses, including molecular dynamics simulations, support a contribution of electrostatic interactions, presumably by arginine residues, to binding and specificity. Collectively, the results presented here and previously support an induced fit and substantial movement of the CTD upon ligand binding and, possibly, during catalysis. To the best of our knowledge, we here present the first structure of a Meprin β holoenzyme containing a zinc ion and a specific inhibitor bound to the active site. The structural data will guide rational drug design and the discovery of highly potent Meprin inhibitors.

Cantilever-centric mechanism of cooperative non-active site mutations in HIV protease: Implications for flap dynamics

The HIV-1 protease is an important drug target in antiretroviral therapy due to the crucial role it plays in viral maturation. A greater understanding of the dynamics of the protease as a result of drug-induced mutations has been successfully elucidated using computational models in the past. We performed induced-fit docking studies and molecular dynamics simulations on the wild-type South African HIV-1 subtype C protease and two non-active site mutation-containing protease variants; HP3 PR and HP4 PR. The HP3 PR contained the I13V, I62V, and V77I mutations while HP4 PR contained the same mutations with the addition of the L33F mutation. The simulations were initiated in a cubic cell universe containing explicit solvent, with the protease variants beginning in the fully closed conformation. The trajectory for each simulation totalled 50 ns. The results indicate that the mutations increase the dynamics of the flap, hinge, fulcrum and cantilever regions when compared to the wild-type protease while in complex with protease inhibitors. Specifically, these mutations result in the protease favouring the semi-open conformation when in complex with inhibitors. Moreover, the HP4 PR adopted curled flap tip conformers which coordinated several water molecules into the active site in a manner that may reduce inhibitor binding affinity. The mutations affected the thermodynamic landscape of inhibitor binding as there were fewer observable chemical contacts between the mutated variants and saquinavir, atazanavir and darunavir. These data help to elucidate the biophysical basis for the selection of cooperative non-active site mutations by the HI virus.

Structural Analysis of the Simultaneous Activation and Inhibition of γ-Secretase Activity in the Development of Drugs for Alzheimer's Disease

Significance: The majority of the drugs which target membrane-embedded protease γ-secretase show an unusual biphasic activation–inhibition dose-response in cells, model animals, and humans. Semagacestat and avagacestat are two biphasic drugs that can facilitate cognitive decline in patients with Alzheimer’s disease. Initial mechanistic studies showed that the biphasic drugs, and pathogenic mutations, can produce the same type of changes in γ-secretase activity. Results: DAPT, semagacestat LY-411,575, and avagacestat are four drugs that show different binding constants, and a biphasic activation–inhibition dose-response for amyloid-β-40 products in SH-SY5 cells. Multiscale molecular dynamics studies have shown that all four drugs bind to the most mobile parts in the presenilin structure, at different ends of the 29 Å long active site tunnel. The biphasic dose-response assays are a result of the modulation of γ-secretase activity by the concurrent binding of multiple drug molecules at each end of the active site tunnel. The drugs activate γ-secretase by facilitating the opening of the active site tunnel, when the rate-limiting step is the tunnel opening, and the formation of the enzyme–substrate complex. The drugs inhibit γ-secretase as uncompetitive inhibitors by binding next to the substrate, to dynamic enzyme structures which regulate processive catalysis. The drugs can modulate the production of different amyloid-β catalytic intermediates by penetration into the active site tunnel, to different depths, with different flexibility and different binding affinity. Conclusions: Biphasic drugs and pathogenic mutations can affect the same dynamic protein structures that control processive catalysis. Successful drug-design strategies must incorporate transient changes in the γ-secretase structure in the development of specific modulators of its catalytic activity.

Conformational Changes of Glutamine 5'-Phosphoribosylpyrophosphate Amidotransferase for Two Substrates Analogue Binding: Insight from Conventional Molecular Dynamics and Accelerated Molecular Dynamics Simulations

Glutamine 5′-phosphoribosylpyrophosphate amidotransferase (GPATase) catalyzes the synthesis of phosphoribosylamine, pyrophosphate, and glutamate from phosphoribosylpyrophosphate, as well as glutamine at two sites (i.e., glutaminase and phosphoribosylpyrophosphate sites), through a 20 Å NH₃ channel. In this study, conventional molecular dynamics (cMD) simulations and enhanced sampling accelerated molecular dynamics (aMD) simulations were integrated to characterize the mechanism for coordination catalysis at two separate active sites in the enzyme. Results of cMD simulations illustrated the mechanism by which two substrate analogues, namely, DON and cPRPP, affect the structural stability of GPATase from the perspective of dynamic behavior. aMD simulations obtained several key findings. First, a comparison of protein conformational changes in the complexes of GPATase–DON and GPATase–DON–cPRPP showed that binding cPRPP to the PRTase flexible loop (K326 to L350) substantially effected the formation of the R73-DON salt bridge. Moreover, only the PRTase flexible loop in the GPATase–DON–cPRPP complex could remain closed and had sufficient space for cPRPP binding, indicating that binding of DON to the glutamine loop had an impact on the PRTase flexible loop. Finally, both DON and cPRPP tightly bonded to the two domains, thereby inducing the glutamine loop and the PRTase flexible loop to move close to each other. This movement facilitated the transfer of NH3 via the NH3 channel. These theoretical results are useful to the ongoing research on efficient inhibitors related to GPATase.

Biochemical and structural characterization of two cif-like epoxide hydrolases from Burkholderia cenocepacia

Epoxide hydrolases catalyze the conversion of epoxides to vicinal diols in a range of cellular processes such as signaling, detoxification, and virulence. These enzymes typically utilize a pair of tyrosine residues to orient the substrate epoxide ring in the active site and stabilize the hydrolysis intermediate. A new subclass of epoxide hydrolases that utilize a histidine in place of one of the tyrosines was established with the discovery of the CFTR Inhibitory Factor (Cif) from Pseudomonas aeruginosa. Although the presence of such Cif-like epoxide hydrolases was predicted in other opportunistic pathogens based on sequence analyses, only Cif and its homolog aCif from Acinetobacter nosocomialis have been characterized. Here we report the biochemical and structural characteristics of Cfl1 and Cfl2, two Cif-like epoxide hydrolases from Burkholderia cenocepacia. Cfl1 is able to hydrolyze xenobiotic as well as biological epoxides that might be encountered in the environment or during infection. In contrast, Cfl2 shows very low activity against a diverse set of epoxides. The crystal structures of the two proteins reveal quaternary structures that build on the well-known dimeric assembly of the α/β hydrolase domain, but broaden our understanding of the structural diversity encoded in novel oligomer interfaces. Analysis of the interfaces reveals both similarities and key differences in sequence conservation between the two assemblies, and between the canonical dimer and the novel oligomer interfaces of each assembly. Finally, we discuss the effects of these higher-order assemblies on the intra-monomer flexibility of Cfl1 and Cfl2 and their possible roles in regulating enzymatic activity.

p53 Is Potentially Regulated by Cyclophilin D in the Triple-Proline Loop of the DNA Binding Domain

The multifunctional protein p53 is the central molecular sensor of cellular stresses. The canonical function of p53 is to transcriptionally activate target genes in response to, for example, DNA damage that may trigger apoptosis. Recently, p53 was also found to play a role in the regulation of necrosis, another type of cell death featured by the mitochondrial permeability transition (mPT). In this process, p53 directly interacts with the mPT regulator cyclophilin D, the detailed mechanism of which however remains poorly understood. Here, we report a comprehensive computational investigation of the p53-cyclophilin D interaction using molecular dynamics simulations and associated analyses. We have identified the specific cyclophilin D binding site on p53 that is located at proline 151 in the DNA binding domain. As a peptidyl-prolyl isomerase, cyclophilin D binds p53 and catalyzes the cis-trans isomerization of the peptide bond preceding proline 151. We have also characterized the effect of such an isomerization and found that the p53 domain in the cis state is overall more rigid than the trans state except for the local region around proline 151. Dynamical changes upon isomerization occur in both local and distal regions, indicating an allosteric effect elicited by the isomerization. We present potential allosteric communication pathways between proline 151 and distal sites, including the DNA binding surface. Our work provides, for the first time, a model for how cyclophilin D binds p53 and regulates its activity by switching the configuration of a specific site.

Stabilizing AqdC, a Pseudomonas Quinolone Signal-Cleaving Dioxygenase from Mycobacteria, by FRESCO-Based Protein Engineering

The mycobacterial PQS dioxygenase AqdC, a cofactor-less protein with an α/β-hydrolase fold, inactivates the virulence-associated quorum-sensing signal molecule 2-heptyl-3-hydroxy-4(1H)-quinolone (PQS) produced by the opportunistic pathogen Pseudomonas aeruginosa and is therefore a potential anti-virulence tool. We have used computational library design to predict stabilizing amino acid replacements in AqdC. While 57 out of 91 tested single substitutions throughout the protein led to stabilization, as judged by increases in T app m of >2 °C, they all impaired catalytic activity. Combining substitutions, the proteins AqdC-G40K-A134L-G220D-Y238W and AqdC-G40K-G220D-Y238W showed extended half-lives and the best trade-off between stability and activity, with increases in T app m of 11.8 and 6.1 °C and relative activities of 22 and 72 %, respectively, compared to AqdC. Molecular dynamics simulations and principal component analysis suggested that stabilized proteins are less flexible than AqdC, and the loss of catalytic activity likely correlates with an inability to effectively open the entrance to the active site.

Pathogenic mutations in the kinesin-3 motor KIF1A diminish force generation and movement through allosteric mechanisms

The kinesin-3 motor KIF1A functions in neurons, where its fast and superprocessive motility facilitates long-distance transport, but little is known about its force-generating properties. Using optical tweezers, we demonstrate that KIF1A stalls at an opposing load of ~3 pN but more frequently detaches at lower forces. KIF1A rapidly reattaches to the microtubule to resume motion due to its class-specific K-loop, resulting in a unique clustering of force generation events. To test the importance of neck linker docking in KIF1A force generation, we introduced mutations linked to human neurodevelopmental disorders. Molecular dynamics simulations predict that V8M and Y89D mutations impair neck linker docking. Indeed, both mutations dramatically reduce the force generation of KIF1A but not the motor’s ability to rapidly reattach to the microtubule. Although both mutations relieve autoinhibition of the full-length motor, the mutant motors display decreased velocities, run lengths, and landing rates and delayed cargo transport in cells. These results advance our understanding of how mutations in KIF1A can manifest in disease.

Weakening of interaction networks with aging in tip-link protein induces hearing loss

Age-related hearing loss (ARHL) is a common condition in humans marking the gradual decrease in hearing with age. Perturbations in the tip-link protein cadherin-23 that absorbs the mechanical tension from sound and maintains the integrity of hearing is associated with ARHL. Here, in search of molecular origins for ARHL, we dissect the conformational behavior of cadherin-23 along with the mutant S47P that progresses the hearing loss drastically. Using an array of experimental and computational approaches, we highlight a lower thermodynamic stability, significant weakening in the hydrogen-bond network and inter-residue correlations among β-strands, due to the S47P mutation. The loss in correlated motions translates to not only a remarkable two orders of magnitude slower folding in the mutant but also to a proportionately complex unfolding mechanism. We thus propose that loss in correlated motions within cadherin-23 with aging may trigger ARHL, a molecular feature that likely holds true for other disease-mutations in β-strand-rich proteins.

The impact of proline isomerization on antigen binding and the analytical profile of a trispecific anti-HIV antibody

Proline cis-trans conformational isomerization is a mechanism that affects different types of protein functions and behaviors. Using analytical characterization, structural analysis, and molecular dynamics simulations, we studied the causes of an aberrant two-peak size-exclusion chromatography profile observed for a trispecific anti-HIV antibody. We found that proline isomerization in the tyrosine-proline-proline (YPP) motif in the heavy chain complementarity-determining region (CDR)3 domain of one of the antibody arms (10e8v4) was a component of this profile. The pH effect on the conformational equilibrium that led to these two populations was presumably caused by a histidine residue (H147) in the light chain that is in direct contact with the YPP motif. Finally, we demonstrated that, due to chemical equilibrium between the cis and trans proline conformers, the antigen-binding potency of the trispecific anti-HIV antibody was not significantly affected in spite of a potential structural clash of 10e8v4 YP_transP_trans conformers with the membrane-proximal ectodomain region epitope in the GP41 antigen. Altogether, these results reveal at mechanistic and molecular levels the effect of proline isomerization in the CDR on the antibody binding and analytical profiles, and support further development of the trispecific anti-HIV antibody.

Cellular prion protein gene polymorphisms linked to differential scrapie susceptibility correlate with distinct residue connectivity between secondary structure elements

The conformational conversion of the cellular prion protein (PrP^C) to the misfolded and aggregated isoform, termed scrapie prion protein (PrP^Sc), is key to the development of a group of neurodegenerative diseases known as transmissible spongiform encephalopathies (TSEs). Although the conversion mechanism is not fully understood, the role of gene polymorphisms in varying susceptibilities to prion diseases is well established. In ovine, specific gene polymorphisms in PrP^C alter prion disease susceptibility: the Valine136-Glutamine171 variant (Susceptible structure) displays high susceptibility to classical scrapie while the Alanine136-Arginine171 variant (Resistant structure) displays reduced susceptibility. The opposite trend has been reported in atypical scrapie. Despite the differentiation between classical and atypical scrapie, a complete understanding of the effect of polymorphisms on the structural dynamics of PrP^C is lacking. From our structural bioinformatics study, we propose that polymorphisms locally modulate the network of residue interactions in the globular C-terminus of the ovine recombinant prion protein while maintaining the overall fold. Although the two variants we examined exhibit a densely connected group of residues that includes both β-sheets, the β2-α2 loop and the N-terminus of α-helix 2, only in the Resistant structure do most residues of α-helix 2 belong to this group. We identify the structural role of Valine136Alanine and Glutamine171Arginine: modulation of residue interaction networks that affect the connectivity between α-helix 2 and α-helix 3. We propose blocking interactions of residue 171 as a potential target for the design of therapeutics to prevent efficient PrP^C misfolding. We discuss our results in the context of initial PrP^C conversion and extrapolate to recently proposed PrP^Sc structures.Communicated by Ramaswamy H. Sarma.

Exploring interfacial dynamics in homodimeric S-ribosylhomocysteine lyase (LuxS) from Vibrio cholerae through molecular dynamics simulations

To the best of our knowledge, this is the first molecular dynamics simulation study on the dimeric form of the LuxS enzyme from Vibrio cholerae to evaluate its structural and dynamical properties including the dynamics of the interface formed by the two monomeric chains of the enzyme. The dynamics of the interfacial region were investigated in terms of inter-residual contacts and the associated interface area of the enzyme in its ligand-free and ligand–bound states which produced characteristics contrast in the interfacial dynamics. Moreover, the binding patterns of the two inhibitors (RHC and KRI) to the enzyme forming two different enzyme–ligand complexes were analyzed which pointed towards a varying inhibition potential of the inhibitors as also revealed by the free energies of ligand binding. It is shown that KRI is a more potent inhibitor than RHC – a substrate analogue, showing correlation with experimental data. Moreover, the role of a loop in chain B of the enzyme was found to facilitate the binding of RHC similar to that of the substrate, while KRI demonstrates a differing binding pattern. The computation of the free energy of binding for the two ligands was also carried out via thermodynamic integration which ultimately served to correlate the dynamical properties with the inhibition potential of two different ligands against the enzyme. Furthermore, this successful study provides a rational to suggest novel LuxS inhibitors which could become promising candidates to treat the diseases caused by a broad variety of bacterial species.

To the best of our knowledge, this is the first molecular dynamics simulation study on the dimeric form of the LuxS enzyme from Vibrio cholerae to evaluate its structural and dynamical properties including the dynamics of the interface formed by the two monomeric chains of the enzyme.

Heart Failure Drug Modifies the Intrinsic Dynamics of the Pre-Power Stroke State of Cardiac Myosin

Omecamtiv mecarbil (OM), currently investigated for the treatment of heart failure, is the first example of a new class of drugs (cardiac myotropes) that can modify muscle contractility by directly targeting sarcomeric proteins. Using atomistic molecular dynamics simulations, we show that the binding of OM to the pre-power stroke state of cardiac myosin inhibits the functional motions of the protein and potentially affects Pi release from the nucleotide binding site. We also show that the changes in myosin ATPase activity induced by a set of OM analogues can be predicted from their relative affinity to the pre-power stroke state compared to the near rigor one, indicating that conformational selectivity plays an important role in determining the activity of these compounds.

Quantification of the Resilience and Vulnerability of HIV-1 Native Glycan Shield at Atomistic Detail

Dense surface glycosylation on the HIV-1 envelope (Env) protein acts as a shield from the adaptive immune system. However, the molecular complexity and flexibility of glycans make experimental studies a challenge. Here we have integrated high-throughput atomistic modeling of fully glycosylated HIV-1 Env with graph theory to capture immunologically important features of the shield topology. This is the first complete all-atom model of HIV-1 Env SOSIP glycan shield that includes both oligomannose and complex glycans, providing physiologically relevant insights of the glycan shield. This integrated approach including quantitative comparison with cryo-electron microscopy data provides hitherto unexplored details of the native shield architecture and its difference from the high-mannose glycoform. We have also derived a measure to quantify the shielding effect over the antigenic protein surface that defines regions of relative vulnerability and resilience of the shield and can be harnessed for rational immunogen design.

Molecular determinant of substrate binding and specificity of cytochrome P450 2J2

Cytochrome P450 2J2 (CYP2J2) is responsible for the epoxidation of endogenous arachidonic acid, and is involved in the metabolism of exogenous drugs. To date, no crystal structure of CYP2J2 is available, and the proposed structural basis for the substrate recognition and specificity in CYP2J2 varies with the structural models developed using different computational protocols. In this study, we developed a new structural model of CYP2J2, and explored its sensitivity to substrate binding by molecular dynamics simulations of the interactions with chemically similar fluorescent probes. Our results showed that the induced-fit binding of these probes led to the preferred active poses ready for the catalysis by CYP2J2. Divergent conformational dynamics of CYP2J2 due to the binding of each probe were observed. However, a stable hydrophobic clamp composed of residues I127, F310, A311, V380, and I487 was identified to restrict any substrate access to the active site of CYP2J2. Molecular docking of a series of compounds including amiodarone, astemizole, danazol, ebastine, ketoconazole, terfenadine, terfenadone, and arachidonic acid to CYP2J2 confirmed the role of those residues in determining substrate binding and specificity of CYP2J2. In addition to the flexibility of CYP2J2, the present work also identified other factors such as electrostatic potential in the vicinity of the active site, and substrate strain energy and property that have implications for the interpretation of CYP2J2 metabolism.

Tyrosine in the hinge region of the pore-forming motif regulates oligomeric β-barrel pore formation by Vibrio cholerae cytolysin

β-barrel pore-forming toxins perforate cell membranes by forming oligomeric β-barrel pores. The most crucial step is the membrane-insertion of the pore-forming motifs that create the transmembrane β-barrel scaffold. Molecular mechanism that regulates structural reorganization of these pore-forming motifs during β-barrel pore-formation still remains elusive. Using Vibrio cholerae cytolysin as an archetypical example of the β-barrel pore-forming toxin, we show that a key tyrosine residue (Y321) in the hinge region of the pore-forming motif plays crucial role in this process. Mutation of Y321 abrogates oligomerization of the membrane-bound toxin protomers, and blocks subsequent steps of pore-formation. Our study suggests that the presence of Y321 in the hinge region of the pore-forming motif is crucial for the toxin molecule to sense membrane-binding, and to trigger essential structural rearrangements required for the subsequent oligomerization and pore-formation process. Such a regulatory mechanism of pore-formation by V. cholerae cytolysin has not been documented earlier in the structurally related β-barrel pore-forming toxins.

Ebola Virus VP35 Protein: Modeling of the Tetrameric Structure and an Analysis of Its Interaction with Human PKR

The Viral Protein 35 (VP35), a crucial protein of the Zaire Ebolavirus (EBOV), interacts with a plethora of human proteins to cripple the human immune system. Despite its importance, the entire structure of the tetrameric assembly of EBOV VP35 and the means by which it antagonizes the autophosphorylation of the kinase domain of human protein kinase R (PKRK) is still elusive. We consult existing structural information to model a tetrameric assembly of the VP35 protein where 93% of the protein is modeled using crystal structure templates. We analyze our modeled tetrameric structure to identify interchain bonding networks and use molecular dynamics simulations and normal-mode analysis to unravel the flexibility and deformability of the different regions of the VP35 protein. We establish that the C-terminal of VP35 (VP35C) directly interacts with PKRK to prevent it from autophosphorylation. Further, we identify three plausible VP35C-PKRK complexes with better affinity than the PKRK dimer formed during autophosphorylation and use protein design to establish a new stretch in VP35C that interacts with PKRK. The proposed tetrameric assembly will aid in better understanding of the VP35 protein, and the reported VP35C-PKRK complexes along with their interacting sites will help in the shortlisting of small molecule inhibitors.

Crystallographic and molecular dynamics simulation analysis of NAD synthetase from methicillin resistant Staphylococcus aureus (MRSA)

NAD synthetase (NadE) catalyzes the last step in NAD biosynthesis, transforming deamido-NAD⁺ into NAD⁺ by a two-step reaction with co-substrates ATP and amide donor ammonia. In this study, we report the crystal structure of Staphylococcus aureus NAD synthetase enzyme (saNadE) at 2.3 Å resolution. We used this structure to perform molecular dynamics simulations of apo-enzyme, enzyme-substrate (NadE with ATP and NaAD) and enzyme-intermediate complexes (NadE with NaAD-AMP) to investigate key binding interactions and explore the conformational transitions and flexibility of the binding pocket. Our results show large shift of N-terminal region in substrate bound form which is important for ATP binding. Substrates drive the correlated movement of loop regions surrounding it as well as some regions distal to the active site and stabilize them at complex state. Principal component analysis of atomic projections distinguish feasible trajectories to delineate distinct motions in enzyme-substrate to enzyme-intermediate states. Our results suggest mixed binding involving dominant induced fit and conformational selection. MD simulation extracted ensembles of NadE could potentially be utilized for in silico screening and structure based design of more effective Methicillin Resistant Staphylococcus aureus (MRSA) inhibitors.

Computational Design of Nitrile Hydratase from Pseudonocardia thermophila JCM3095 for Improved Thermostability

High thermostability and catalytic activity are key properties for nitrile hydratase (NHase, EC 4.2.1.84) as a well-industrialized catalyst. In this study, rational design was applied to tailor the thermostability of NHase from Pseudonocardia thermophila JCM3095 (PtNHase) by combining FireProt server prediction and molecular dynamics (MD) simulation. Site-directed mutagenesis of non-catalytic residues provided by the rational design was subsequentially performed. The positive multiple-point mutant, namely, M10 (αI5P/αT18Y/αQ31L/αD92H/βA20P/βP38L/βF118W/βS130Y/βC189N/βC218V), was obtained and further analyzed. The Melting temperature (T_m) of the M10 mutant showed an increase by 3.2 °C and a substantial increase in residual activity of the enzyme at elevated temperatures was also observed. Moreover, the M10 mutant also showed a 2.1-fold increase in catalytic activity compared with the wild-type PtNHase. Molecular docking and MD simulations demonstrated better substrate affinity and improved thermostability for the mutant.

Comparative ligand structural analytics illustrated on variably glycosylated MUC1 antigen-antibody binding

When faced with the investigation of the preferential binding of a series of ligands against a known target, the solution is not always evident from single structure analysis. An ensemble of structures generated from computer simulations is valuable; however, visual analysis of the extensive structural data can be overwhelming. Rapid analysis of trajectory data, with tools available in the Galaxy platform, can be used to understand key features and compare differences that inform the preferential ligand structure that favors binding. We illustrate this informatics approach by investigating the in-silico binding of a peptide and glycopeptide epitope of the glycoprotein Mucin 1 (MUC1) binding with the antibody AR20.5. To study the binding, we performed molecular dynamics simulations using OpenMM and then used the Galaxy platform for data analysis. The same analysis tools are applied to each of the simulation trajectories and this process was streamlined by using Galaxy workflows. The conformations of the antigens were analyzed using root-mean-square deviation, end-to-end distance, Ramachandran plots, and hydrogen bonding analysis. Additionally, RMSF and clustering analysis were carried out. These analyses were used to rapidly assess key features of the system, interrogate the dynamic structure of the ligand, and determine the role of glycosylation on the conformational equilibrium. The glycopeptide conformations in solution change relative to the peptide; thus a partially pre-structuring is seen prior to binding. Although the bound conformation of peptide and glycopeptide is similar, the glycopeptide fluctuates less and resides in specific conformers for more extended periods. This structural analysis which gives a high-level view of the features in the system under observation, could be readily applied to other binding problems as part of a general strategy in drug design or mechanistic analysis.

Effects of Nucleotide and End-Dependent Actin Conformations on Polymerization

The regulation of actin is key for controlled cellular function. Filaments are regulated by actin-binding proteins, but the nucleotide state of actin is also an important factor. From extended molecular dynamics simulations, we find that both nucleotide states of the actin monomer have significantly less twist than their crystal structures and that the ATP monomer is flatter than the ADP form. We also find that the filament's pointed end is flatter than the remainder of the filament and has a conformation distinct from G-actin, meaning that incoming monomers would need to undergo isomerization that would weaken the affinity and slow polymerization. Conversely, the barbed end of the filament takes on a conformation nearly identical to the ATP monomer, enhancing ATP G-actin's ability to polymerize as compared with ADP G-actin. The thermodynamic penalty imposed by differences in isomerization for the ATP and ADP growth at the barbed end exactly matches experimental results.

Intuitive, reproducible high-throughput molecular dynamics in Galaxy: a tutorial

This paper is a tutorial developed for the data analysis platform Galaxy. The purpose of Galaxy is to make high-throughput computational data analysis, such as molecular dynamics, a structured, reproducible and transparent process. In this tutorial we focus on 3 questions: How are protein-ligand systems parameterized for molecular dynamics simulation? What kind of analysis can be carried out on molecular trajectories? How can high-throughput MD be used to study multiple ligands? After finishing you will have learned about force-fields and MD parameterization, how to conduct MD simulation and analysis for a protein-ligand system, and understand how different molecular interactions contribute to the binding affinity of ligands to the Hsp90 protein.

Tyrosine Nitration Contributes to Nitric Oxide-Stimulated Degradation of CYP2B6

Human cytochrome P450 (P450) CYP2B6 undergoes nitric oxide (NO)-dependent proteasomal degradation in response to the NO donor dipropylenetriamine NONOate (DPTA) and biologic NO in HeLa and HuH7 cell lines. CYP2B6 is also downregulated by NO in primary human hepatocytes. We hypothesized that NO or derivative reactive nitrogen species may generate adducts of tyrosine and/or cysteine residues, causing CYP2B6 downregulation, and selected Tyr and Cys residues for mutation based on predicted solvent accessibility. CYP2B6V5-Y317A, -Y380A, and -Y190A mutant proteins expressed in HuH7 cells were less sensitive than wild-type (WT) enzyme to degradation evoked by DPTA, suggesting that these tyrosines are targets for NO-dependent downregulation. The Y317A or Y380A mutants did not show increases in high molecular mass (HMM) species after treatment with DPTA or bortezomib + DPTA, in contrast to the WT enzyme. Carbon monoxide-releasing molecule 2 treatment caused rapid suppression of 2B6 enzyme activity, significant HMM species generation, and ubiquitination of CYP2B6 protein but did not stimulate CYP2B6 degradation. The CYP2B6 inhibitor 4-(4-chlorophenyl)imidazole blocked NO-dependent CYP2B6 degradation, suggesting that NO access to the active site is important. Molecular dynamics simulations predicted that tyrosine nitrations of CYP2B6 would cause significant destabilizing perturbations of secondary structure and remove correlated motions likely required for enzyme function. We propose that cumulative nitrations of Y190, Y317, and Y380 by reactive nitrogen species cause destabilization of CYP2B6, which may act synergistically with heme nitrosylation to target the enzyme for degradation. SIGNIFICANCE STATEMENT: This work provides novel insight into the mechanisms by which nitric oxide, which is produced in hepatocytes in response to inflammation, triggers the ubiquitin-dependent proteasomal degradation of the cytochrome P450 (P450) enzyme CYP2B6. Our data demonstrate that both nitration of specific tyrosine residues and interaction of nitric oxide (NO) with the P450 heme are necessary for NO to trigger ubiquitination and protein degradation.

Identification of potential allosteric binding sites in cathepsin K based on intramolecular communication

Network theory methods and molecular dynamics (MD) simulations are accepted tools to study allosteric regulation. Indeed, dynamic networks built upon correlation analysis of MD trajectories provide detailed information about communication paths between distant sites. In this context, we aimed to understand whether the efficiency of intramolecular communication could be used to predict the allosteric potential of a given site. To this end, we performed MD simulations and network theory analyses in cathepsin K (catK), whose allosteric sites are well defined. To obtain a quantitative measure of the efficiency of communication, we designed a new protocol that enables the comparison between properties related to ensembles of communication paths obtained from different sites. Further, we applied our strategy to evaluate the allosteric potential of different catK cavities not yet considered for drug design. Our predictions of the allosteric potential based on intramolecular communication correlate well with previous catK experimental and theoretical data. We also discuss the possibility of applying our approach to other proteins from the same family.

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/.

An in silico approach to identification, categorization and prediction of nucleic acid binding proteins

The interaction between proteins and nucleic acid plays an important role in many processes, such as transcription, translation and DNA repair. The mechanisms of related biological events can be understood by exploring the function of proteins in these interactions. The number of known protein sequences has increased rapidly in recent years, but the databases for describing the structure and function of protein have unfortunately grown quite slowly. Thus, improving such databases is meaningful for predicting protein-nucleic acid interactions. Furthermore, the mechanism of related biological events, such as viral infection or designing novel drug targets, can be further understood by understanding the function of proteins in these interactions. The information for each sequence, including its function and interaction sites, were collected and identified, and a database called PNIDB was built. The proteins in PNIDB were grouped into 27 classes, such as transcription, immune system, and structural protein, etc. The function of each protein was then predicted using a machine learning method. Using our method, the predictor was trained on labeled sequences, and then the function of a protein was predicted based on the trained classifier. The prediction accuracy achieved a score of 77.43% by 10-fold cross validation.

Investigating the pathogenic SNPs in BLM helicase and their biological consequences by computational approach

The BLM helicase protein plays a vital role in DNA replication and the maintenance of genomic integrity. Variation in the BLM helicase gene resulted in defects in the DNA repair mechanism and was reported to be associated with Bloom syndrome (BS) and cancer. Despite extensive investigation of helicase proteins in humans, no attempt has previously been made to comprehensively analyse the single nucleotide polymorphism (SNPs) of the BLM gene. In this study, a comprehensive analysis of SNPs on the BLM gene was performed to identify, characterize and validate the pathogenic SNPs using computational approaches. We obtained SNP data from the dbSNP database version 150 and mapped these data to the genomic coordinates of the "NM_000057.3" transcript expressing BLM helicase (P54132). There were 607 SNPs mapped to missense, 29 SNPs mapped to nonsense, and 19 SNPs mapped to 3'-UTR regions. Initially, we used many consensus tools of SIFT, PROVEAN, Condel, and PolyPhen-2, which together increased the accuracy of prediction and identified 18 highly pathogenic non-synonymous SNPs (nsSNPs) out of 607 SNPs. Subsequently, these 18 high-confidence pathogenic nsSNPs were analysed for BLM protein stability, structure-function relationships and disease associations using various bioinformatics tools. These 18 mutants of the BLM protein along with the native protein were further investigated using molecular dynamics simulations to examine the structural consequences of the mutations, which might reveal their malfunction and contribution to disease. In addition, 28 SNPs were predicted as "stop gained" nonsense SNPs and one SNP was predicted as "start lost". Two SNPs in the 3'UTR were found to abolish miRNA binding and thus may enhance the expression of BLM. Interestingly, we found that BLM mRNA overexpression is associated with different types of cancers. Further investigation showed that the dysregulation of BLM is associated with poor overall survival (OS) for lung and gastric cancer patients and hence led to the conclusion that BLM has the potential to be used as an important prognostic marker for the detection of lung and gastric cancer.

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.

Computation-aided engineering of starch-debranching pullulanase from Bacillus thermoleovorans for enhanced thermostability

Pullulanases are widely used in food, medicine, and other industries because they specifically hydrolyze α-1,6-glycosidic linkages in starch and oligosaccharides. In addition, high-temperature thermostable pullulanase has multiple advantages, including decreasing saccharification solution viscosity accompanied with enhanced mass transfer and reducing microbial contamination in starch hydrolysis. However, thermophilic pullulanase availability remains limited. Additionally, most do not meet starch-manufacturing requirements due to weak thermostability. Here, we developed a computation-aided strategy to engineer the thermophilic pullulanase from Bacillus thermoleovorans. First, three computational design predictors (FoldX, I-Mutant 3.0, and dDFIRE) were combined to predict stability changes introduced by mutations. After excluding conserved and catalytic sites, 17 mutants were identified. After further experimental verification, we confirmed six positive mutants. Among them, the G692M mutant had the highest thermostability improvement, with 3.8 °C increased T_m and 2.1-fold longer half-life than the wild type at 70 °C. We then characterized the mechanism underlying increased thermostability, such as rigidity enhancement, closer conformation, and strengthened motion correlation using root mean square fluctuation (RMSF), principal component analysis (PCA), dynamic cross-correlation map (DCCM), and free energy landscape (FEL) analysis. KEY POINTS: • A computation-aided strategy was developed to engineer pullulanase thermostability. • Seventeen mutants were identified by combining three computational design predictors. • The G692M mutant was obtained with increased T_mand half-life at 70 °C.

Revealing the selective mechanisms of inhibitors to PARP-1 and PARP-2 via multiple computational methods

Background

Research has shown that Poly-ADP-ribose polymerases 1 (PARP-1) is a potential therapeutic target in the clinical treatment of breast cancer. An increasing number of studies have focused on the development of highly selective inhibitors that target PARP-1 over PARP-2, its closest isoform, to mitigate potential side effects. However, due to the highly conserved and similar binding sites of PARP-1 and PARP-2, there is a huge challenge for the discovery and design of PARP-1 inhibitors. Recently, it was reported that a potent PARP-1 inhibitor named NMS-P118 exhibited greater selectivity to PARP-1 over PARP-2 compared with a previously reported drug (Niraparib). However, the mechanisms underlying the effect of this inhibitor remains unclear.

Methods

In the present study, classical molecular dynamics (MD) simulations and accelerated molecular dynamics (aMD) simulations combined with structural and energetic analysis were used to investigate the structural dynamics and selective mechanisms of PARP-1 and PARP-2 that are bound to NMS-P118 and Niraparib with distinct selectivity.

Results

The results from classical MD simulations indicated that the selectivity of inhibitors may be controlled by electrostatic interactions, which were mainly due to the residues of Gln-322, Ser-328, Glu-335, and Tyr-455 in helix αF. The energetic differences were corroborated by the results from aMD simulations.

Conclusion

This study provides new insights about how inhibitors specifically bind to PARP-1 over PARP-2, which may help facilitate the design of highly selective PARP-1 inhibitors in the future.

Discovery of Human Signaling Systems: Pairing Peptides to G Protein-Coupled Receptors

The peptidergic system is the most abundant network of ligand-receptor-mediated signaling in humans. However, the physiological roles remain elusive for numerous peptides and more than 100 G protein-coupled receptors (GPCRs). Here we report the pairing of cognate peptides and receptors. Integrating comparative genomics across 313 species and bioinformatics on all protein sequences and structures of human class A GPCRs, we identify universal characteristics that uncover additional potential peptidergic signaling systems. Using three orthogonal biochemical assays, we pair 17 proposed endogenous ligands with five orphan GPCRs that are associated with diseases, including genetic, neoplastic, nervous and reproductive system disorders. We also identify additional peptides for nine receptors with recognized ligands and pathophysiological roles. This integrated computational and multifaceted experimental approach expands the peptide-GPCR network and opens the way for studies to elucidate the roles of these signaling systems in human physiology and disease.

Video Abstract

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Universal characteristics enabled prediction of peptide ligands and receptors

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Multifaceted screening enabled detection of pathway- and assay-dependent responses

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Peptide ligands discovered for BB₃, GPR1, GPR15, GPR55, and GPR68

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Each signaling system is a link to human physiology and is associated with disease

KinaMetrix: a web resource to investigate kinase conformations and inhibitor space

Protein kinases are among the most explored protein drug targets. Visualization of kinase conformations is critical for understanding structure–function relationship in this family and for developing chemically unique, conformation-specific small molecule drugs. We have developed Kinformation, a random forest classifier that annotates the conformation of over 3500 protein kinase structures in the Protein Data Bank. Kinformation was trained on structural descriptors derived from functionally important motifs to automatically categorize kinases into five major conformations with pharmacological relevance. Here we present KinaMetrix (http://KinaMetrix.com), a web resource enabling researchers to investigate the protein kinase conformational space as well as a subset of kinase inhibitors that exhibit conformational specificity. KinaMetrix allows users to classify uploaded kinase structures, as well as to derive structural descriptors of protein kinases. Uploaded structures can then be compared to atomic structures of other kinases, enabling users to identify kinases that occupy a similar conformational space to their uploaded structure. Finally, KinaMetrix also serves as a repository for both small molecule substructures that are significantly associated with each conformation type, and for homology models of kinases in inactive conformations. We expect KinaMetrix to serve as a resource for researchers studying kinase structural biology or developing conformation-specific kinase inhibitors.

Long-range Regulation of Partially Folded Amyloidogenic Peptides

Neurodegeneration involves abnormal aggregation of intrinsically disordered amyloidogenic peptides (IDPs), usually mediated by hydrophobic protein-protein interactions. There is mounting evidence that formation of α-helical intermediates is an early event during self-assembly of amyloid-β42 (Aβ42) and α-synuclein (αS) IDPs in Alzheimer’s and Parkinson’s disease pathogenesis, respectively. However, the driving force behind on-pathway molecular assembly of partially folded helical monomers into helical oligomers assembly remains unknown. Here, we employ extensive molecular dynamics simulations to sample the helical conformational sub-spaces of monomeric peptides of both Aβ42 and αS. Our computed free energies, population shifts, and dynamic cross-correlation network analyses reveal a common feature of long-range intra-peptide modulation of partial helical folds of the amyloidogenic central hydrophobic domains via concerted coupling with their charged terminal tails (N-terminus of Aβ42 and C-terminus of αS). The absence of such inter-domain fluctuations in both fully helical and completely unfolded (disordered) states suggests that long-range coupling regulates the dynamicity of partially folded helices, in both Aβ42 and αS peptides. The inter-domain coupling suggests a form of intra-molecular allosteric regulation of the aggregation trigger in partially folded helical monomers. This approach could be applied to study the broad range of amyloidogenic peptides, which could provide a new path to curbing pathogenic aggregation of partially folded conformers into oligomers, by inhibition of sites far from the hydrophobic core.

A beginner's guide to molecular dynamics simulations and the identification of cross-correlation networks for enzyme engineering

The functional properties of proteins are decided not only by their relatively rigid overall structures, but even more importantly, by their dynamic properties. In a protein, some regions of structure exhibit highly correlated or anti-correlated motions with others, some are highly dynamic but uncorrelated, while other regions are relatively static. The residues with correlated or anti-correlated motions can form a so-called dynamic cross-correlation network, through which information can be transmitted. Such networks have been shown to be critical to allosteric transitions, and ligand binding, and have also been shown to be able to mediate epistatic interactions between mutations. As a result, they are likely to play a significant role in the development of new enzyme engineering strategies. In this chapter, protocols are provided for the assessment of dynamic cross-correlation networks, and for their application in protein engineering. Transketolase from E. coli is used as a model and the software GROMACS is applied for carrying out MD simulations to generate trajectories containing structural ensembles. The trajectory is then used for a dynamic cross correlation analysis using the R package, Bio3D. A matrix of all atom-wise cross-correlation coefficients is finally obtained, which can be displayed in a graphical representation termed a dynamical cross-correlation matrix.

Revealing Acquired Resistance Mechanisms of Kinase-Targeted Drugs Using an on-the-Fly, Function-Site Interaction Fingerprint Approach

Although kinase-targeted drugs have achieved significant clinical success, they are frequently subject to the limitations of drug resistance, which has become a primary vulnerability to targeted drug therapy. Therefore, deciphering resistance mechanisms is an important step in designing more efficacious, antiresistant drugs. Here we studied two FDA-approved kinase drugs: Crizotinib and Ceritinib, which are first- and second-generation anaplastic lymphoma kinase (ALK) targeted inhibitors, to unravel drug-resistance mechanisms. We used an on-the-fly, function-site interaction fingerprint (on-the-fly Fs-IFP) approach, combining binding free-energy surface calculations with the Fs-IFPs. Establishing the potentials of mean force and monitoring the atomic-scale protein-ligand interactions, before and after L1196M-induced drug resistance, revealed insights into drug-resistance/antiresistant mechanisms. Crizotinib prefers to bind the wild-type ALK kinase domain, whereas Ceritinib binds more favorably to the mutated ALK kinase domain, in agreement with experimental results. We determined that ALK kinase-drug interactions in the region of the front pocket are associated with drug resistance. Additionally, we find that the L1196M mutation does not simply alter the binding modes of inhibitors but also affects the flexibility of the entire ALK kinase domain. Our work provides an understanding of the mechanisms of ALK drug resistance, confirms the usefulness of the on-the-fly Fs-IFP approach, and provides a practical paradigm to study drug-resistance mechanisms in prospective drug discovery.

Peptide cargo tunes a network of correlated motions in human leucocyte antigens

Most biomolecular interactions are typically thought to increase the (local) rigidity of a complex, for example, in drug‐target binding. However, detailed analysis of specific biomolecular complexes can reveal a more subtle interplay between binding and rigidity. Here, we focussed on the human leucocyte antigen (HLA), which plays a crucial role in the adaptive immune system by presenting peptides for recognition by the αβ T‐cell receptor (TCR). The role that the peptide plays in tuning HLA flexibility during TCR recognition is potentially crucial in determining the functional outcome of an immune response, with obvious relevance to the growing list of immunotherapies that target the T‐cell compartment. We have applied high‐pressure/temperature perturbation experiments, combined with molecular dynamics simulations, to explore the drivers that affect molecular flexibility for a series of different peptide–HLA complexes. We find that different peptide sequences affect peptide–HLA flexibility in different ways, with the peptide cargo tuning a network of correlated motions throughout the pHLA complex, including in areas remote from the peptide‐binding interface, in a manner that could influence T‐cell antigen discrimination.

Structure and mechanism of pyrimidine-pyrimidone (6-4) photoproduct recognition by the Rad4/XPC nucleotide excision repair complex

Failure in repairing ultraviolet radiation-induced DNA damage can lead to mutations and cancer. Among UV-lesions, the pyrimidine–pyrimidone (6-4) photoproduct (6-4PP) is removed from the genome much faster than the cyclobutane pyrimidine dimer (CPD), owing to the more efficient recognition of 6-4PP by XPC-RAD23B, a key initiator of global-genome nucleotide excision repair (NER). Here, we report a crystal structure of a Rad4–Rad23 (yeast XPC-Rad23B ortholog) bound to 6-4PP-containing DNA and 4-μs molecular dynamics (MD) simulations examining the initial binding of Rad4 to 6-4PP or CPD. This first structure of Rad4/XPC bound to a physiological substrate with matched DNA sequence shows that Rad4 flips out both 6-4PP-containing nucleotide pairs, forming an ‘open’ conformation. The MD trajectories detail how Rad4/XPC initiates ‘opening’ 6-4PP: Rad4 initially engages BHD2 to bend/untwist DNA from the minor groove, leading to unstacking and extrusion of the 6-4PP:AA nucleotide pairs towards the major groove. The 5′ partner adenine first flips out and is captured by a BHD2/3 groove, while the 3′ adenine extrudes episodically, facilitating ensuing insertion of the BHD3 β-hairpin to open DNA as in the crystal structure. However, CPD resists such Rad4-induced structural distortions. Untwisting/bending from the minor groove may be a common way to interrogate DNA in NER.

How Different Substitution Positions of F, Cl Atoms in Benzene Ring of 5-Methylpyrimidine Pyridine Derivatives Affect the Inhibition Ability of EGFRL858R/T790M/C797S Inhibitors: A Molecular Dynamics Simulation Study

Lung cancer is the most frequent cause of cancer-related deaths worldwide, and mutations in the kinase domain of the epidermal growth factor receptor (EGFR) are a common cause of non-small-cell lung cancers, which is a major subtype of lung cancers. Recently, a series of 5-methylpyrimidine-pyridinone derivatives have been designed and synthesized as novel selective inhibitors of EGFR and EGFR mutants. However, the binding-based inhibition mechanism has not yet been determined. In this study, we carried out molecular dynamic simulations and free-energy calculations for EGFR derivatives to fill this gap. Based on the investigation, the three factors that influence the inhibitory effect of inhibitors are as follows: (1) The substitution site of the Cl atom is the main factor influencing the activity through steric effect; (2) The secondary factors are repulsion between the F atom (present in the inhibitor) and Glu762, and the blocking effect of Lys745 on the phenyl ring of the inhibitor. (3) The two factors function synergistically to influence the inhibitory capacity of the inhibitor. The theoretical results of this study can provide further insights that will aid the design of oncogenic EGFR inhibitors with high selectivity.

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.