Thermodynamic and molecular dynamic insights into how fusion influences peptide-tag recognition of an antibody.

To understand the effect of protein fusion on the recognition of a peptide-tag by an antibody, we fused a CCR5-derived peptide-tag (pep1) to GFP and investigated its recognition by an anti-pep1 antibody, 4B08. First, to characterize the thermodynamic properties associated with the pep1-4B08 binding, isothermal titration calorimetry experiments were conducted. It was found that pep1 fused to the C-terminus of GFP (GFP-CT) enhanced the enthalpic gain by 2.1 kcal mol-1 and the entropic loss only by 0.9 kcal mol-1, resulting in an 8-fold increase in the binding affinity compared to the unfused pep1. On the other hand, pep1 fused to the N-terminus of GFP (GFP-NT) enhanced the enthalpic gain by 3.0 kcal mol-1 and the entropic loss by 3.2 kcal mol-1, leading to no significant enhancement of the binding affinity. To gain deeper insights, molecular dynamics simulations of GFP-NT, GFP-CT, and pep1 were performed. The results showed that the location of the fusion point sensitively affects the interaction energy, the solvent accessible surface area, and the fluctuation of pep1 in the unbound state, which explains the difference in the experimental thermodynamic properties.

Role of tubulin C-terminal tail on mechanical properties of microtubule.

Tubulin C-terminal tail (CTT) is a disordered segment extended from each tubulin monomer of αß tubulin heterodimers, the building blocks of microtubules. The tubulin CTT contributes to the cellular function of microtubules such as intracellular transportation by regulating their interaction with other proteins and cell shape regulation by controlling microtubule polymerization dynamics. Although the mechanical integrity of microtubules is crucial for their functions, the role of tubulin CTT on microtubule mechanical properties has remained elusive. In this work, we investigate the role of tubulin CTTs in regulating the mechanical properties of microtubules by estimating the persistence lengths and investigating the buckling behavior of microtubules with and without CTT. We find that microtubules with intact CTTs exhibit twice the rigidity of microtubules lacking tubulin CTTs. Our study will widen the scope of altering microtubule mechanical properties for its application in nano bio-devices and lead to novel therapeutic approaches for neurodegenerative diseases with altered microtubule properties.

Classification of the HCN isomerization reaction dynamics in Ar buffer gas via machine learning.

The effect of the presence of Ar on the isomerization reaction HCN ⇄ CNH is investigated via machine learning. After the potential energy surface function is developed based on the CCSD(T)/aug-cc-pVQZ level ab initio calculations, classical trajectory simulations are performed. Subsequently, with the aim of extracting insights into the reaction dynamics, the obtained reactivity, that is, whether the reaction occurs or not under a given initial condition, is learned as a function of the initial positions and momenta of all the atoms in the system. The prediction accuracy of the trained model is greater than 95%, indicating that machine learning captures the features of the phase space that affect reactivity. Machine learning models are shown to successfully reproduce reactivity boundaries without any prior knowledge of classical reaction dynamics theory. Subsequent analyses reveal that the Ar atom affects the reaction by displacing the effective saddle point. When the Ar atom is positioned close to the N atom (resp. the C atom), the saddle point shifts to the CNH (HCN) region, which disfavors the forward (backward) reaction. The results imply that analyses aided by machine learning are promising tools for enhancing the understanding of reaction dynamics.

Tensile Stress Reduction and Strain Concentration of Epoxy Resin Caused by Heterogeneity: A Multiscale Approach Combining Molecular Dynamics Simulation and Finite Element Method.

In this study, we investigated the effect of heterogeneity on the mechanical properties of epoxy resin by combining coarse-grained molecular dynamics (CG-MD) and finite element method (FEM) simulations. To evaluate the heterogeneity effect in the uniaxial elongation, heterogeneous and homogeneous FEM models of micrometer-scale cubic epoxy resin were constructed. For the heterogeneous FEM model, parameters of nanometer-scale elements were determined by CG-MD simulations, where nanometer-scale blocks have different cross-linked structures. For the homogeneous FEM model, the averaged parameters were used for all elements. The calculated stress-strain (S-S) curves of the heterogeneous model exhibit similar tensile stress values when compared to the experimental data, whereas the homogeneous model yields notably higher values. Moreover, a clear strain concentration associated with the formation of the shear band-like structure was observed in the heterogeneous model and not in the homogeneous model.

Molecular Dynamics Simulation for Investigating Antigen-Antibody Interaction.

Molecular dynamics (MD) simulation is a computational method which elucidates the protein dynamics. Following analyses characterize the dynamics and structural change as well as interaction energy. To characterize the protein structure effectively, the internal angular coordinates are often useful. Directional analysis provides the averages and variances of those coordinates in a mathematically rigorous way. Here, we describe not only a standard MD simulation procedure for the antigen-antibody system but also an umbrella sampling method following a multistep targeted MD simulation (US/mTMD), which is useful for evaluating the free energy profile along the antigen-antibody dissociation coordinate.

Pathological complete remission of relapsed tumor by photo-activating antibody-mimetic drug conjugate treatment.

Antibody-mimetic drug conjugate is a novel noncovalent conjugate consisting of an antibody-mimetic recognizing a target molecule on the cancer cell surface and low-molecular-weight payloads that kill the cancer cells. In this study, the efficacy of a photo-activating antibody-mimetic drug conjugate targeting HER2-expressing tumors was evaluated in mice, by using the affibody that recognize HER2 (ZHER2:342 ) as a target molecule and an axially substituted silicon phthalocyanine (a novel potent photo-activating compound) as a payload. The first treatment with the photo-activating antibody-mimetic drug conjugates reduced the size of all HER2-expressing KPL-4 xenograft tumors macroscopically. However, during the observation period, relapsed tumors gradually appeared in approximately 50% of the animals. To evaluate the efficacy of repeated antibody-mimetic drug conjugate treatment, animals with relapsed tumors were treated again with the same regimen. After the second observation period, the mouse tissues were examined histopathologically. Unexpectedly, all relapsed tumors were eradicated, and all animals were diagnosed with pathological complete remission. After the second treatment, skin wounds healed rapidly, and no significant side effects were observed in other organs, except for occasional microscopic granulomatous tissues beneath the serosa of the liver in a few mice. Repeated treatments seemed to be well tolerated. These results indicate the promising efficacy of the repeated photo-activating antibody-mimetic drug conjugate treatment against HER2-expressing tumors.

Antibody mimetic drug conjugate manufactured by high-yield Escherichia coli expression and non-covalent binding system.

Antibody-drug conjugates (ADCs) are a major therapeutic tool for the treatment of advanced cancer. Malignant cells in advanced cancer often display multiple genetic mutations and become resistant to monotherapy. Therefore, a therapeutic regimen that simultaneously targets multiple molecules with multiple payloads is desirable. However, the development of ADCs is hampered by issues in biopharmaceutical manufacturing and the complexity of the conjugation process of low-molecular-weight payloads to biologicals. Here, we report antibody mimetic-drug conjugates (AMDCs) developed by exploiting the non-covalent binding property of payloads based on high-affinity binding of mutated streptavidin and modified iminobiotin. Miniprotein antibodies were fused to a low immunogenic streptavidin variant, which was then expressed in Escherichia coli inclusion bodies, solubilized, and refolded into functional tetramers. The AMDC developed against human epidermal growth factor receptor 2 (HER2) effectively killed cultured cancer cells using bis-iminobiotin conjugated to photo-activating silicon phthalocyanine. The HER2-targeting AMDC was also effective in vivo against a mouse KPL-4 xenograft model. This AMDC platform provides rapid, stable, and high-yield therapeutics against multiple targets.

Deformation of microtubules regulates translocation dynamics of kinesin.

Microtubules, the most rigid components of the cytoskeleton, can be key transduction elements between external forces and the cellular environment. Mechanical forces induce microtubule deformation, which is presumed to be critical for the mechanoregulation of cellular events. However, concrete evidence is lacking. In this work, with high-speed atomic force microscopy, we unravel how microtubule deformation regulates the translocation of the microtubule-associated motor protein kinesin-1, responsible for intracellular transport. Our results show that the microtubule deformation by bending impedes the translocation dynamics of kinesins along them. Molecular dynamics simulation shows that the hindered translocation of kinesins can be attributed to an enhanced affinity of kinesins to the microtubule structural units in microtubules deformed by bending. This study advances our understanding of the role of cytoskeletal components in mechanotransduction.

Environmental Effects on Salt Bridge Stability in the Protein-Protein Interface: The Case of Hen Egg-White Lysozyme and Its Antibody, HyHEL-10.

We studied the stability of two salt bridges between hen egg-white lysozyme (HEL) and its antibody, HyHEL-10, by using molecular dynamics simulations. It was observed that one salt bridge, D32H-K97Y, was stable, whereas the other, D99H-K97Y, was not. To understand this difference, we compared several reduced salt bridge models that incorporated the salt bridges and nearby residues. The results showed the importance of nearby residues, especially Y33H and W98H. Furthermore, to understand the effects of nearby salt bridges, we investigated two mutants, D32HA and D99HA. We found that the D32HA mutation considerably stabilized the D99H-K97Y salt bridge. The reduced model analysis indicated that this can be largely attributed to a conformational change of the main chain.

Modification and Validation of the DREIDING Force Field for Molecular Liquid Simulations (DREIDING-UT).

In this study, we modified Lennard-Jones (LJ) parameters and point-charge parameters of the DREIDING force field (the modified force-field model is named DREIDING-UT). While the original LJ parameters of DREIDING were derived through an analytical formula to reproduce the potential depths and the equilibrium lengths of the Buckingham potentials of DREIDING/X6, the modified LJ parameters were derived through the least square fitting of the Buckingham potentials. Because the Gasteiger-Marsili (GM) charges of the original DREIDING underestimated electrostatic interactions, we replaced it with the restrained electrostatic potential (RESP) charges calculated from the ab initio wavefunctions, taking the dynamic electron correlation and solvation effects into account. To confirm how the modified force field works, we conducted molecular dynamics (MD) simulations of typical liquids. It was found that the densities and self-diffusion coefficients of the DREIDING-UT model agreed with the experimental ones much better than those of the original model.

Cupid and Psyche system for the diagnosis and treatment of advanced cancer.

In advanced cancer patients, malignant cells invade and disseminate within normal cells and develop resistance to therapy with additional genetic mutations, which makes radical cure very difficult. Precision medicine against advanced cancer is hampered by the lack of systems aimed at multiple target molecules within multiple loci. Here, we report the development of a versatile diagnostic and therapeutic system for advanced cancer, named the Cupid and Psyche system. Based on the strong non-covalent interaction of streptavidin and biotin, a low immunogenic mutated streptavidin, Cupid, and a modified artificial biotin, Psyche, have been designed. Cupid can be fused with various single-chain variable fragment antibodies and forms tetramer to recognize cancer cells precisely. Psyche can be conjugated to a wide range of diagnostic and therapeutic agents against malignant cells. The Cupid and Psyche system can be used in pre-targeting therapy as well as photo-immunotherapy effectively in animal models supporting the concept of a system for precision medicine for multiple targets within multiple loci.

Convergence in LINE-1 nucleotide variations can benefit redundantly forming triplexes with lncRNA in mammalian X-chromosome inactivation.

BACKGROUND: Associations between X-inactive transcript (Xist)-long noncoding RNA (lncRNA) and chromatin are critical intermolecular interactions in the X-chromosome inactivation (XCI) process. Despite high-resolution analyses of the Xist RNA-binding sites, specific interaction sequences are yet to be identified. Based on elusive features of the association between Xist RNA and chromatin and the possible existence of multiple low-affinity binding sites in Xist RNA, we defined short motifs (≥5 nucleotides), termed as redundant UC/TC (r-UC/TC) or AG (r-AG) motifs, which may help in the mediation of triplex formation between the lncRNAs and duplex DNA. RESULTS: The study showed that r-UC motifs are densely dispersed throughout mouse and human Xist/XIST RNAs, whereas r-AG motifs are even more densely dispersed along opossum RNA-on-the-silent X (Rsx) RNA, and also along both full-length and truncated long interspersed nuclear elements (LINE-1s, L1s) of the three species. Predicted secondary structures of the lncRNAs showed that the length range of these sequence motifs available for forming triplexes was even shorter, mainly 5- to 9-nucleotides long. Quartz crystal microbalance (QCM) measurements and Monte Carlo (MC) simulations indicated that minimum-length motifs can reinforce the binding state by increasing the copy number of the motifs in the same RNA or DNA molecule. Further, r-AG motifs in L1s had a similar length-distribution pattern, regardless of the similarities in the length or sequence of L1s across the three species; this also applies to high-frequency mutations in r-AG motifs, which suggests convergence in L1 sequence variations. CONCLUSIONS: Multiple short motifs in both RNA and duplex DNA molecules could be brought together to form triplexes with either Hoogsteen or reverse Hoogsteen hydrogen bonding, by which their associations are cooperatively enhanced. This novel triplex interaction could be involved in associations between lncRNA and chromatin in XCI, particularly at the sites of L1s. Potential binding of Xist/XIST/Rsx RNAs specifically at L1s is most likely preserved through the r-AG motifs conserved in mammalian L1s through convergence in L1 nucleotide variations and by maintaining a particular r-UC/r-AG motif ratio in each of these lncRNAs, irrespective of their poorly conserved sequences.

A SNP in a Steroidogenic Enzyme Is Associated with Phenotypic Sex in Seriola Fishes.

Vertebrate sex development consists largely of two processes: "sex determination," the initial bifurcation of sexual identity, and "sex differentiation," which subsequently facilitates maleness or femaleness according to the sex determination signal. Steroid hormones promote multiple types of sexual dimorphism in eutherian mammals and avians [1-3], in which they are indispensable for proper sex differentiation. By contrast, in many poikilothermic vertebrates, steroid hormones have been proposed to be key players in sex determination as well as sex differentiation [4-8]. This hypothesis was introduced more than 50 years ago but has never been rigorously tested due to difficulties in discriminating the roles of steroids in sex determination and differentiation. We found that a missense SNP in the gene encoding the steroidogenic enzyme 17ß-hydroxysteroid dehydrogenase 1 (Hsd17b1) was perfectly associated with ZZ/ZW sex determination in Seriola fishes. Biochemical analyses revealed that a glutamate residue present specifically in Z-type HSD17B1 attenuated interconversion between 17-keto and 17ß-hydroxy steroids relative to the allelic product from the W chromosome, which harbors glycine at that position, by disrupting the hydrogen bond network between the steroid and the enzyme's catalytic residues. Hsd17b1 mRNA is constitutively expressed in undifferentiated and differentiating gonads of both genotypic sexes, whereas W-type mRNA is expressed only in genotypic females. Meanwhile, Cyp19a1 is predominantly expressed in differentiating ovary. We conclude that the combination of Hsd17b1 alleles determines sex by modulating endogenous estrogen levels in Seriola species. These findings strongly support the long-standing hypothesis on steroids in sex determination.

Affinity Improvement of a Cancer-Targeted Antibody through Alanine-Induced Adjustment of Antigen-Antibody Interface.

To investigate favorable single amino acid substitutions that improve antigen-antibody interactions, alanine (Ala) mutagenesis scanning of the interfacial residues of a cancer-targeted antibody, B5209B, was performed based on X-ray crystallography analysis. Two substitutions were shown to significantly enhance the binding affinity for the antigen, by up to 30-fold. One substitution improved the affinity by a gain of binding enthalpy, whereas the other substitution improved the affinity by a gain of binding entropy. Molecular dynamics simulations showed that the enthalpic improvement could be attributed to the stabilization of distant salt bridges located at the periphery of the antigen-antibody interface. The entropic improvement was due to the release of water molecules that were stably trapped in the antigen-antibody interface of the wild-type antibody. Importantly, these effects of the Ala substitutions were caused by subtle adjustments of the binding interface. These results will be helpful to design high-affinity antibodies with avoiding entropy-enthalpy compensation.

Tyrosine Sulfation Restricts the Conformational Ensemble of a Flexible Peptide, Strengthening the Binding Affinity for an Antibody.

Protein tyrosine sulfation (PTS) is a post-translational modification regulating numerous biological events. PTS generally occurs at flexible regions of proteins, enhancing intermolecular interactions between proteins. Because of the high flexibility associated with the regions where PTS is generally encountered, an atomic-level understanding has been difficult to achieve by X-ray crystallography or nuclear magnetic resonance techniques. In this study, we focused on the conformational behavior of a flexible sulfated peptide and its interaction with an antibody. Molecular dynamics simulations and thermodynamic analysis indicated that PTS reduced the main-chain fluctuations upon the appearance of sulfate-mediated intramolecular H-bonds. Collectively, our data suggested that one of the mechanisms by which PTS may enhance protein-protein interactions consists of the limitation of conformational dynamics in the unbound state, thus reducing the loss of entropy upon binding and boosting the affinity for its partner.

Toward rational antibody design: recent advancements in molecular dynamics simulations.

Because antibodies have become an important therapeutic tool, rational antibody design is a challenging issue involving various science and technology fields. From the computational aspect, many types of design-assist methods have been developed, but their accuracy is not fully satisfactory. Because of recent advancements in computational power, molecular dynamics (MD) simulation has become a helpful tool to trace the motion of proteins and to characterize their properties. Thus, MD simulation has been applied to various systems involving antigen-antibody complexes and has been shown to provide accurate insight into antigen-antibody interactions and dynamics at an atomic resolution. Therefore, it is highly possible that MD simulation will play several roles complementing the conventional antibody design. In this review, we address several important features of MD simulation in the context of rational antibody design.

Molecular dynamics analysis to evaluate docking pose prediction.

The accurate prediction of a ligand-protein complex structure is important for computer-assisted drug development. Although many docking methods have been developed over the last three decades, the success of binding structure prediction remains greatly limited. The purpose of this study was to demonstrate the usefulness of molecular dynamics (MD) simulation in assessing a docking pose predicted using a docking program. If the predicted pose is not unstable in an aqueous environment, MD simulation equilibrates the system and removes the ligand from the predicted position. Here we investigated two proteins that are important potential therapeutic targets: ß2 adrenergic receptor (ß2AR) and PR-Set7. While ß2AR is rigid and its ligands are very similar to the template ligand (carazolol), PR-Set7 is very flexible and its ligands vary greatly from the template ligand (histone H4 tail peptide). On an empirical basis, we usually expect that the docking prediction is accurate when the protein is rigid and its ligands are similar to the template ligand. The MD analyses in this study clearly suggested such a tendency. Furthermore, we discuss the possibility that the MD simulation can predict the binding pose of a ligand.

The feasibility of an efficient drug design method with high-performance computers.

In this study, we propose a supercomputer-assisted drug design approach involving all-atom molecular dynamics (MD)-based binding free energy prediction after the traditional design/selection step. Because this prediction is more accurate than the empirical binding affinity scoring of the traditional approach, the compounds selected by the MD-based prediction should be better drug candidates. In this study, we discuss the applicability of the new approach using two examples. Although the MD-based binding free energy prediction has a huge computational cost, it is feasible with the latest 10 petaflop-scale computer. The supercomputer-assisted drug design approach also involves two important feedback procedures: The first feedback is generated from the MD-based binding free energy prediction step to the drug design step. While the experimental feedback usually provides binding affinities of tens of compounds at one time, the supercomputer allows us to simultaneously obtain the binding free energies of hundreds of compounds. Because the number of calculated binding free energies is sufficiently large, the compounds can be classified into different categories whose properties will aid in the design of the next generation of drug candidates. The second feedback, which occurs from the experiments to the MD simulations, is important to validate the simulation parameters. To demonstrate this, we compare the binding free energies calculated with various force fields to the experimental ones. The results indicate that the prediction will not be very successful, if we use an inaccurate force field. By improving/validating such simulation parameters, the next prediction can be made more accurate.

Structural features of interfacial tyrosine residue in ROBO1 fibronectin domain-antibody complex: Crystallographic, thermodynamic, and molecular dynamic analyses.

ROBO1, fibronectin Type-III domain (Fn)-containing protein, is a novel immunotherapeutic target for hepatocellular carcinoma in humans. The crystal structure of the antigen-binding fragment (Fab) of B2212A, the monoclonal antibody against the third Fn domain (Fn3) of ROBO1, was determined in pursuit of antibody drug for hepatocellular carcinoma. This effort was conducted in the presence or absence of the antigen, with the chemical features being investigated by determining the affinity of the antibody using molecular dynamics (MD) and thermodynamics. The structural comparison of B2212A Fab between the complex and the free form revealed that the interfacial Tyr(L) 50 (superscripts L, H, and F stand for the residues in the light chain, heavy chain, and Fn3, respectively) played important roles in Fn3 recognition. That is, the aromatic ring of Tyr(L) 50 pivoted toward Phe(F) 68, forming a CH/π interaction and a new hydrogen bond with the carbonyl O atom of Phe(F) 68. MD simulations predicted that the Tyr(L) 50-Phe(F) 68 interaction almost entirely dominated Fab-Fn3 binding, and Ala-substitution of Tyr(L) 50 led to a reduced binding of the resultant complex. On the contrary, isothermal titration calorimetry experiments underscored that Ala-substitution of Tyr(L) 50 caused an increase of the binding enthalpy between B2212A and Fn3, but importantly, it induced an increase of the binding entropy, resulting in a suppression of loss in the Gibbs free energy in total. These results suggest that mutation analysis considering the binding entropy as well as the binding enthalpy will aid in the development of novel antibody drugs for hepatocellular carcinoma.

Molecular dynamics simulation-based evaluation of the binding free energies of computationally designed drug candidates: importance of the dynamical effects.

The computational structure-based drug design (SBDD) mainly aims at generating or discovering new chemical compounds with sufficiently large binding free energy. In any de novo drug design methods and virtual screening methods, drug candidates are selected by approximately evaluating the binding free energy (or the binding affinity). This approximate binding free energy, usually called "empirical score," is critical to the success of the SBDD. The purpose of this work is to yield physical insight into the approximate evaluation method in comparison with an exact molecular dynamics (MD) simulation-based method (named MP-CAFEE), which can predict binding free energies accurately. We calculate the binding free energies for 58 selected drug candidates with MP-CAFEE. Here, the compounds are generated by OPMF, a novel fragment-based de novo drug design method, and the ligand-protein interaction energy is used as an empirical score. The results show that the correlation between the binding free energy and the interaction energy is not strong enough to clearly distinguish compounds with nM-affinity from those with µM-affinity. This implies that it is necessary to take into account the natural protein motion with explicitly surrounded by water molecules to improve the efficiency of the drug candidate selection procedure.