Conformational Selectivity of ITK Inhibitors: Insights from Molecular Dynamics Simulations.

Interleukin-2-inducible T-cell kinase (ITK) regulates the response to T-cell receptor signaling and is a drug target for inflammatory and immunological diseases. Molecules that bind preferentially to the active form of ITK have low selectivity between kinases, whereas those that bind preferentially to the inactive form have high selectivity for ITK. Therefore, computational methods to predict the conformational selectivity of compounds are required to design highly selective ITK inhibitors. In this study, we performed absolute binding free-energy perturbation (ABFEP) simulations for 11 compounds on both active and inactive forms of ITK, and the calculated binding free energies were compared with experimental data. The conformational selectivity of 10 of the 11 compounds was correctly predicted using ABFEP. To investigate the mechanism underlying the stabilization of the active and inactive structures by the compounds, we performed extensive, conventional molecular dynamics simulations, which revealed that the compound-induced stabilization of the P-loop and linkage of conformational changes in L489, V419, F501, and M410 upon compound binding were critical factors. A guideline for designing inactive-form binders is proposed based on these key structural factors. The ABFEP and the created guidelines are expected to facilitate the discovery of highly selective ITK inhibitors.

Structural basis for ligand recognition and signaling of hydroxy-carboxylic acid receptor 2.

Hydroxycarboxylic acid receptors (HCAR1, HCAR2, and HCAR3) transduce Gi/o signaling upon biding to molecules such as lactic acid, butyric acid and 3-hydroxyoctanoic acid, which are associated with lipolytic and atherogenic activity, and neuroinflammation. Although many reports have elucidated the function of HCAR2 and its potential as a therapeutic target for treating not only dyslipidemia but also neuroimmune disorders such as multiple sclerosis and Parkinson's disease, the structural basis of ligand recognition and ligand-induced Gi-coupling remains unclear. Here we report three cryo-EM structures of the human HCAR2-Gi signaling complex, each bound with different ligands: niacin, acipimox or GSK256073. All three agonists are held in a deep pocket lined by residues that are not conserved in HCAR1 and HCAR3. A distinct hairpin loop at the HCAR2 N-terminus and extra-cellular loop 2 (ECL2) completely enclose the ligand. These structures also reveal the agonist-induced conformational changes propagated to the G-protein-coupling interface during activation. Collectively, the structures presented here are expected to help in the design of ligands specific for HCAR2, leading to new drugs for the treatment of various diseases such as dyslipidemia and inflammation.

Comparison of the Molecular Motility of Tubulin Dimeric Isoforms: Molecular Dynamics Simulations and Diffracted X-ray Tracking Study.

Tubulin has been recently reported to form a large family consisting of various gene isoforms; however, the differences in the molecular features of tubulin dimers composed of a combination of these isoforms remain unknown. Therefore, we attempted to elucidate the physical differences in the molecular motility of these tubulin dimers using the method of measurable pico-meter-scale molecular motility, diffracted X-ray tracking (DXT) analysis, regarding characteristic tubulin dimers, including neuronal TUBB3 and ubiquitous TUBB5. We first conducted a DXT analysis of neuronal (TUBB3-TUBA1A) and ubiquitous (TUBB5-TUBA1B) tubulin dimers and found that the molecular motility around the vertical axis of the neuronal tubulin dimer was lower than that of the ubiquitous tubulin dimer. The results of molecular dynamics (MD) simulation suggest that the difference in motility between the neuronal and ubiquitous tubulin dimers was probably caused by a change in the major contact of Gln245 in the T7 loop of TUBB from Glu11 in TUBA to Val353 in TUBB. The present study is the first report of a novel phenomenon in which the pico-meter-scale molecular motility between neuronal and ubiquitous tubulin dimers is different.

Dynamic Solution Structures of Whole Human NAP1 Dimer Bound to One and Two Histone H2A-H2B Heterodimers Obtained by Integrative Methods.

Nucleosome assembly protein 1 (NAP1) binds to histone H2A-H2B heterodimers, mediating their deposition on and eviction from the nucleosome. Human NAP1 (hNAP1) consists of a dimerization core domain and intrinsically disordered C-terminal acidic domain (CTAD), both of which are essential for H2A-H2B binding. Several structures of NAP1 proteins bound to H2A-H2B exhibit binding polymorphisms of the core domain, but the distinct structural roles of the core and CTAD domains remain elusive. Here, we have examined dynamic structures of the full-length hNAP1 dimer bound to one and two H2A-H2B heterodimers by integrative methods. Nuclear magnetic resonance (NMR) spectroscopy of full-length hNAP1 showed CTAD binding to H2A-H2B. Atomic force microscopy revealed that hNAP1 forms oligomers of tandem repeated dimers; therefore, we generated a stable dimeric hNAP1 mutant exhibiting the same H2A-H2B binding affinity as wild-type hNAP1. Size exclusion chromatography (SEC), multi-angle light scattering (MALS) and small angle X-ray scattering (SAXS), followed by modelling and molecular dynamics simulations, have been used to reveal the stepwise dynamic complex structures of hNAP1 binding to one and two H2A-H2B heterodimers. The first H2A-H2B dimer binds mainly to the core domain of hNAP1, while the second H2A-H2B binds dynamically to both CTADs. Based on our findings, we present a model of the eviction of H2A-H2B from nucleosomes by NAP1.

TLR3 forms a laterally aligned multimeric complex along double-stranded RNA for efficient signal transduction.

Toll-like receptor 3 (TLR3) is a member of the TLR family, which plays an important role in the innate immune system and is responsible for recognizing viral double-stranded RNA (dsRNA). Previous biochemical and structural studies have revealed that a minimum length of approximately 40-50 base pairs of dsRNA is necessary for TLR3 binding and dimerization. However, efficient TLR3 activation requires longer dsRNA and the molecular mechanism underlying its dsRNA length-dependent activation remains unknown. Here, we report cryo-electron microscopy analyses of TLR3 complexed with longer dsRNA. TLR3 dimers laterally form a higher multimeric complex along dsRNA, providing the basis for cooperative binding and efficient signal transduction.

Mandibulofacial dysostosis with alopecia results from ETAR gain-of-function mutations via allosteric effects on ligand binding.

Mutations of G protein-coupled receptors (GPCRs) cause various human diseases, but the mechanistic details are limited. Here, we establish p.E303K in the gene encoding the endothelin receptor type A (ETAR/EDNRA) as a recurrent mutation causing mandibulofacial dysostosis with alopecia (MFDA), with craniofacial changes similar to those caused by p.Y129F. Mouse models carrying either of these missense mutations exhibited a partial maxillary-to-mandibular transformation, which was rescued by deleting the ligand endothelin 3 (ET3/EDN3). Pharmacological experiments confirmed the causative ETAR mutations as gain of function, dependent on ET3. To elucidate how an amino acid substitution far from the ligand binding site can increase ligand affinity, we used molecular dynamics (MD) simulations. E303 is located at the intracellular end of transmembrane domain 6, and its replacement by a lysine increased flexibility of this portion of the helix, thus favoring G protein binding and leading to G protein-mediated enhancement of agonist affinity. The Y129F mutation located under the ligand binding pocket reduced the sodium-water network, thereby affecting the extracellular portion of helices in favor of ET3 binding. These findings provide insight into the pathogenesis of MFDA and into allosteric mechanisms regulating GPCR function, which may provide the basis for drug design targeting GPCRs.

Binding and Unbinding Pathways of Peptide Substrates on the SARS-CoV-2 3CL Protease.

Based on many crystal structures of ligand complexes, much study has been devoted to understanding the molecular recognition of SARS-CoV-2 3C-like protease (3CLpro), a potent drug target for COVID-19. In this research, to extend this present static view, we examined the kinetic process of binding/unbinding of an eight-residue substrate peptide to/from 3CLpro by evaluating the path ensemble with the weighted ensemble simulation. The path ensemble showed the mechanism of how a highly flexible peptide folded into the bound form. At the early stage, the dominant motion was the diffusion on the protein surface showing a broad distribution, whose center was led into the cleft of the chymotrypsin fold. We observed a definite sequential formation of the hydrogen bonds at the later stage occurring in the cleft, initiated between Glu166 (3CLpro) and P3_Val (peptide), followed by binding to the oxyanion hole and completed by the sequence-specific recognition at P1_Gln.

Functional dynamics of SARS-CoV-2 3C-like protease as a member of clan PA.

SARS-CoV-2 3C-like protease (3CLpro), a potential therapeutic target for COVID-19, consists of a chymotrypsin fold and a C-terminal α-helical domain (domain III), the latter of which mediates dimerization required for catalytic activation. To gain further understanding of the functional dynamics of SARS-CoV-2 3CLpro, this review extends the scope to the comparative study of many crystal structures of proteases having the chymotrypsin fold (clan PA of the MEROPS database). First, the close correspondence between the zymogen-enzyme transformation in chymotrypsin and the allosteric dimerization activation in SARS-CoV-2 3CLpro is illustrated. Then, it is shown that the 3C-like proteases of family Coronaviridae (the protease family C30), which are closely related to SARS-CoV-2 3CLpro, have the same homodimeric structure and common activation mechanism via domain III mediated dimerization. The survey extended to order Nidovirales reveals that all 3C-like proteases belonging to Nidovirales have domain III, but with various chain lengths, and 3CLpro of family Mesoniviridae (family C107) has the same homodimeric structure as that of C30, even though they have no sequence similarity. As a reference, monomeric 3C proteases belonging to the more distant family Picornaviridae (family C3) lacking domain III are compared with C30, and it is shown that the 3C proteases are rigid enough to maintain their structures in the active state. Supplementary Information: The online version contains supplementary material available at 10.1007/s12551-022-01020-x.

Development of the force field for cyclosporine A.

Membrane permeability of cyclic peptides is an important factor in drug design. To investigate the membrane permeability of cyclic peptides using molecular dynamics (MD) simulations, the accurate force fields for unnatural amino acids present in the cyclic peptides are required. Therefore, we developed the CHARMM force fields of the unnatural amino acids present in cyclosporin A (CsA), a cyclic peptide used as an immune suppressor. Especially for N-methyl amino acids, which contribute to the membrane permeability of cyclic peptides, we developed a grid correction map (CMAP) of the energy surface using the φ and ψ dihedral angles in the main chain of CsA. To validate the developed force field, we performed MD simulations, including the generalized replica exchange with solute tempering method, of CsA in water and chloroform solvents. The conformations of CsA in water and chloroform sampled using the developed force field were consistent with those of the experimental results of the solution nuclear magnetic resonance spectroscopy.

Hybrid in vitro/in silico analysis of low-affinity protein-protein interactions that regulate signal transduction by Sema6D.

Semaphorins constitute a large family of secreted and membrane-bound proteins that signal through cell-surface receptors, plexins. Semaphorins generally use low-affinity protein-protein interactions to bind with their specific plexin(s) and regulate distinct cellular processes such as neurogenesis, immune response, and organogenesis. Sema6D is a membrane-bound semaphorin that interacts with class A plexins. Sema6D exhibited differential binding affinities to class A plexins in prior cell-based assays, but the molecular mechanism underlying this selectivity is not well understood. Therefore, we performed hybrid in vitro/in silico analysis to examine the binding mode of Sema6D to class A plexins and to identify residues that give rise to the differential affinities and thus contribute to the selectivity within the same class of semaphorins. Our biophysical binding analysis indeed confirmed that Sema6D has a higher affinity for Plexin-A1 than for other class A plexins, consistent with the binding selectivity observed in the previous cell-based assays. Unexpectedly, our present crystallographic analysis of the Sema6D-Plexin-A1 complex showed that the pattern of polar interactions is not interaction-specific because it matches the pattern in the prior structure of the Sema6A-Plexin-A2 complex. Thus, we performed in silico alanine scanning analysis and discovered hotspot residues that selectively stabilized the Sema6D-Plexin-A1 pair via Van der Waals interactions. We then validated the contribution of these hotspot residues to the variation in binding affinity with biophysical binding analysis and molecular dynamics simulations on the mutants. Ultimately, our present results suggest that shape complementarity in the binding interfaces is a determinant for binding selectivity.

gr Predictor: A Deep Learning Model for Predicting the Hydration Structures around Proteins.

Among the factors affecting biological processes such as protein folding and ligand binding, hydration, which is represented by a three-dimensional water site distribution function around the protein, is crucial. The typical methods for computing the distribution functions, including molecular dynamics simulations and the three-dimensional reference interaction site model (3D-RISM) theory, require a long computation time ranging from hours to tens of hours. Here, we propose a deep learning (DL) model that rapidly estimates the distribution functions around proteins obtained using the 3D-RISM theory from the protein 3D structure. The distribution functions predicted using our DL model are in good agreement with those obtained using the 3D-RISM theory. Particularly, the coefficient of determination between the distribution function obtained by the DL model and that obtained using the 3D-RISM theory is approximately 0.98. Furthermore, using a graphics processing unit, the prediction by the DL model is completed in less than 1 min, more than 2 orders of magnitude faster than the calculation time of the 3D-RISM theory. The position of water molecules around the protein was estimated based on the distribution function obtained by our DL model, and the position of waters estimated by our DL model was in good agreement with that of water molecules estimated using the 3D-RISM theory and of crystallographic waters. Therefore, our DL model provides a practical and efficient way to calculate the three-dimensional water site distribution functions and to estimate the position of water molecules around the protein. The program called "gr Predictor" is available under the GNU General Public License from https://github.com/YoshidomeGroup-Hydration/gr-predictor.

3D-RISM-AI: A Machine Learning Approach to Predict Protein-Ligand Binding Affinity Using 3D-RISM.

Hydration free energy (HFE) is a key factor in improving protein-ligand binding free energy (BFE) prediction accuracy. The HFE itself can be calculated using the three-dimensional reference interaction model (3D-RISM); however, the BFE predictions solely evaluated using 3D-RISM are not correlated to the experimental BFE for abundant protein-ligand pairs. In this study, to predict the BFE for multiple sets of protein-ligand pairs, we propose a machine learning approach incorporating the HFEs obtained using 3D-RISM, termed 3D-RISM-AI. In the learning process, structural metrics, intra-/intermolecular energies, and HFEs obtained via 3D-RISM of ∼4000 complexes in the PDBbind database (ver. 2018) were used. The BFEs predicted using 3D-RISM-AI were well correlated to the experimental data (Pearson's correlation coefficient of 0.80 and root-mean-square error of 1.91 kcal/mol). As important factors for the prediction, the difference in the solvent accessible surface area between the bound and unbound structures and the hydration properties of the ligands were detected during the learning process.

Structure of SARS-CoV-2 membrane protein essential for virus assembly.

The coronavirus membrane protein (M) is the most abundant viral structural protein and plays a central role in virus assembly and morphogenesis. However, the process of M protein-driven virus assembly are largely unknown. Here, we report the cryo-electron microscopy structure of the SARS-CoV-2 M protein in two different conformations. M protein forms a mushroom-shaped dimer, composed of two transmembrane domain-swapped three-helix bundles and two intravirion domains. M protein further assembles into higher-order oligomers. A highly conserved hinge region is key for conformational changes. The M protein dimer is unexpectedly similar to SARS-CoV-2 ORF3a, a viral ion channel. Moreover, the interaction analyses of M protein with nucleocapsid protein (N) and RNA suggest that the M protein mediates the concerted recruitment of these components through the positively charged intravirion domain. Our data shed light on the M protein-driven virus assembly mechanism and provide a structural basis for therapeutic intervention targeting M protein.

Supramolecular Mechanosensitive Potassium Channel Formed by Fluorinated Amphiphilic Cyclophane.

Inspired by mechanosensitive potassium channels found in nature, we developed a fluorinated amphiphilic cyclophane composed of fluorinated rigid aromatic units connected via flexible hydrophilic octa(ethylene glycol) chains. Microscopic and emission spectroscopic studies revealed that the cyclophane could be incorporated into the hydrophobic layer of the lipid bilayer membranes and self-assembled to form a supramolecular transmembrane ion channel. Current recording measurements using cyclophane-containing planer lipid bilayer membranes successfully demonstrated an efficient transmembrane ion transport. We also demonstrated that the ion transport property was sensitive to the mechanical forces applied to the membranes. In addition, ion transport assays using pH-sensitive fluorescence dye revealed that the supramolecular channel possesses potassium ion selectivity. We also performed all-atom hybrid quantum-mechanical/molecular mechanical simulations to assess the channel structures at atomic resolution and the mechanism of selective potassium ion transport. This research demonstrated the first example of a synthetic mechanosensitive potassium channel, which would open a new door to sensing and manipulating biologically important processes and purification of key materials in industries.

Machine learning to estimate the local quality of protein crystal structures.

Low-resolution electron density maps can pose a major obstacle in the determination and use of protein structures. Herein, we describe a novel method, called quality assessment based on an electron density map (QAEmap), which evaluates local protein structures determined by X-ray crystallography and could be applied to correct structural errors using low-resolution maps. QAEmap uses a three-dimensional deep convolutional neural network with electron density maps and their corresponding coordinates as input and predicts the correlation between the local structure and putative high-resolution experimental electron density map. This correlation could be used as a metric to modify the structure. Further, we propose that this method may be applied to evaluate ligand binding, which can be difficult to determine at low resolution.

Molecular basis of ubiquitin-specific protease 8 autoinhibition by the WW-like domain.

Ubiquitin-specific protease 8 (USP8) is a deubiquitinating enzyme involved in multiple membrane trafficking pathways. The enzyme activity is inhibited by binding to 14-3-3 proteins. Mutations in the 14-3-3-binding motif in USP8 are related to Cushing's disease. However, the molecular basis of USP8 activity regulation remains unclear. This study identified amino acids 645-684 of USP8 as an autoinhibitory region, which might interact with the catalytic USP domain, as per the results of pull-down and single-molecule FRET assays performed in this study. In silico modelling indicated that the region forms a WW-like domain structure, plugs the catalytic cleft, and narrows the entrance to the ubiquitin-binding pocket. Furthermore, 14-3-3 inhibited USP8 activity partly by enhancing the interaction between the WW-like and USP domains. These findings provide the molecular basis of USP8 autoinhibition via the WW-like domain. Moreover, they suggest that the release of autoinhibition may underlie Cushing's disease due to USP8 mutations.

Structure-based screening combined with computational and biochemical analyses identified the inhibitor targeting the binding of DNA Ligase 1 to UHRF1.

The accumulation of epigenetic alterations is one of the major causes of tumorigenesis. Aberrant DNA methylation patterns cause genome instability and silencing of tumor suppressor genes in various types of tumors. Therefore, drugs that target DNA methylation-regulating factors have great potential for cancer therapy. Ubiquitin-like containing PHD and RING finger domain 1 (UHRF1) is an essential factor for DNA methylation maintenance. UHRF1 is overexpressed in various cancer cells and down-regulation of UHRF1 in these cells reactivates the expression of tumor suppressor genes, thus UHRF1 is a promising target for cancer therapy. We have previously shown that interaction between the tandem Tudor domain (TTD) of UHRF1 and DNA ligase 1 (LIG1) di/trimethylated on Lys126 plays a key role in the recruitment of UHRF1 to replication sites and replication-coupled DNA methylation maintenance. An arginine binding cavity (Arg-binding cavity) of the TTD is essential for LIG1 interaction, thus the development of inhibitors that target the Arg-binding cavity could potentially repress UHRF1 function in cancer cells. To develop such an inhibitor, we performed in silico screening using not only static but also dynamic metrics based on all-atom molecular dynamics simulations, resulting in efficient identification of 5-amino-2,4-dimethylpyridine (5A-DMP) as a novel TTD-binding compound. Crystal structure of the TTD in complex with 5A-DMP revealed that the compound stably bound to the Arg-binding cavity of the TTD. Furthermore, 5A-DMP inhibits the full-length UHRF1:LIG1 interaction in Xenopus egg extracts. Our study uncovers a UHRF1 inhibitor which can be the basis of future experiments for cancer therapy.

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.

Allosteric Regulation of 3CL Protease of SARS-CoV-2 and SARS-CoV Observed in the Crystal Structure Ensemble.

The 3C-like protease (3CLpro) of SARS-CoV-2 is a potential therapeutic target for COVID-19. Importantly, it has an abundance of structural information solved as a complex with various drug candidate compounds. Collecting these crystal structures (83 Protein Data Bank (PDB) entries) together with those of the highly homologous 3CLpro of SARS-CoV (101 PDB entries), we constructed the crystal structure ensemble of 3CLpro to analyze the dynamic regulation of its catalytic function. The structural dynamics of the 3CLpro dimer observed in the ensemble were characterized by the motions of four separate loops (the C-loop, E-loop, H-loop, and Linker) and the C-terminal domain III on the rigid core of the chymotrypsin fold. Among the four moving loops, the C-loop (also known as the oxyanion binding loop) causes the order (active)-disorder (collapsed) transition, which is regulated cooperatively by five hydrogen bonds made with the surrounding residues. The C-loop, E-loop, and Linker constitute the major ligand binding sites, which consist of a limited variety of binding residues including the substrate binding subsites. Ligand binding causes a ligand size dependent conformational change to the E-loop and Linker, which further stabilize the C-loop via the hydrogen bond between the C-loop and E-loop. The T285A mutation from SARS-CoV 3CLpro to SARS-CoV-2 3CLpro significantly closes the interface of the domain III dimer and allosterically stabilizes the active conformation of the C-loop via hydrogen bonds with Ser1 and Gly2; thus, SARS-CoV-2 3CLpro seems to have increased activity relative to that of SARS-CoV 3CLpro.