Static Crystal Structures Research Articles

Unveiling the structural mechanisms behind high affinity and selectivity in phosphorylated epitope-specific rabbit antibodies

Protein phosphorylation is a crucial process in various cellular functions, and its irregularities have been implicated in several diseases, including cancer. Antibodies are commonly employed to detect protein phosphorylation in research. However, unlike the extensive studies on recognition mechanisms of the phosphate group by proteins such as kinases and phosphatases, only a few studies have explored antibody mechanisms. In this study, we produced and characterized two rabbit monoclonal antibodies that recognize a mono-phosphorylated Akt peptide. Through crystallography, thermodynamic mutational analyses, and molecular dynamics simulations, we investigated the unique recognition mechanism that enables higher binding affinity and selectivity of the antibodies compared to other generic proteins with lower binding affinity to phosphorylated epitopes. Our results demonstrate that molecular dynamics simulations provide novel insights into the dynamic aspects of molecular recognition of post-translational modifications by proteins beyond static crystal structures, highlighting how specific atomic level interactions drive the exceptional affinity and selectivity of antibodies.

From Static to Dynamic Structures: Improving Binding Affinity Prediction with Graph-Based Deep Learning.

Accurate prediction of protein-ligand binding affinities is an essential challenge in structure-based drug design. Despite recent advances in data-driven methods for affinity prediction, their accuracy is still limited, partially because they only take advantage of static crystal structures while the actual binding affinities are generally determined by the thermodynamic ensembles between proteins and ligands. One effective way to approximate such a thermodynamic ensemble is to use molecular dynamics (MD) simulation. Here, an MD dataset containing 3,218 different protein-ligand complexes is curated, and Dynaformer, a graph-based deep learning model is further developed to predict the binding affinities by learning the geometric characteristics of the protein-ligand interactions from the MD trajectories. In silico experiments demonstrated that the model exhibits state-of-the-art scoring and ranking power on the CASF-2016 benchmark dataset, outperforming the methods hitherto reported. Moreover, in a virtual screening on heat shock protein 90 (HSP90) using Dynaformer, 20 candidates are identified and their binding affinities are further experimentally validated. Dynaformer displayed promising results in virtual drug screening, revealing 12 hit compounds (two are in the submicromolar range), including several novel scaffolds. Overall, these results demonstrated that the approach offer a promising avenue for accelerating the early drug discoveryprocess.

Membrane binding and lipid-protein interaction of the C2 domain from coagulation factor V

Anchoring of coagulation factors to anionic regions of the membrane involves the C2 domain as a key player. The rate of enzymatic reactions of the coagulation factors is increased by several orders of magnitude upon membrane binding. However, the precise mechanisms behind the rate acceleration remain unclear, primarily because of a lack of understanding of the conformational dynamics of the C2-containing factors and corresponding complexes. We elucidate the membrane-bound form of the C2 domain from human coagulation factor V (FV–C2) by characterizing its membrane binding the specific lipid-protein interactions. Employing all-atom molecular dynamics simulations and leveraging the highly mobile membrane-mimetic (HMMM) model, we observed spontaneous binding of FV-C2 to a phosphatidylserine (PS)-containing membrane within 2–25 ns across twelve independent simulations. FV-C2 interacted with the membrane through three loops (spikes 1–3), achieving a converged, stable orientation. Multiple HMMM trajectories of the spontaneous membrane binding provided extensive sampling and ample data to examine the membrane-induced effects on the conformational dynamics of C2 as well as specific lipid-protein interactions. Despite existing crystal structures representing presumed “open” and “closed” states of FV-C2, our results revealed a continuous distribution of structures between these states, with the most populated structures differing from both “open” and “closed” states observed in crystal environments. Lastly, we characterized a putative PS-specific binding site formed by K23, Q48, and S78 located in the groove enclosed by spikes 1–3 (PS-specificity pocket), suggesting a different orientation of a bound headgroup moiety compared to previous proposals based upon analysis of static crystal structures.

Cascading Effect of Large Molecular Motion in Crystals: A Topotactic Polymorphic Transition Paves the Way to Topochemical Polymerization.

A topochemical polymerization governed by a topotactic polymorphic transition is reported. A monomer functionalized with azide and an internal alkyne crystallized as an unreactive polymorph with two molecules in the asymmetric unit. The molecules are aligned in a head-to-head fashion, thereby avoiding the azide-alkyne proximity for the topochemical azide-alkyne cycloaddition (TAAC) reaction. However, upon heating, one of the two conformers underwent a drastic 180° rotation, leading to a single-crystal-to-single-crystal (SCSC) polymorphic transition to a reactive form, wherein the molecules are head-to-tail arranged, ensuring azide-alkyne proximity. The new polymorph underwent TAAC reaction to form a trisubstituted 1,2,3-triazole-linked polymer. These results, showing unexpected topochemical reactivity of a crystal due to the intermediacy of an SCSC polymorphic transition from an unreactive form to a reactive form, highlight that predicting topochemical reactivity by relying on the static crystal structure can be misleading.

FERM domains recruit ample PI(4,5)P2s to form extensive protein-membrane attachments

The four-point-one ezrin-radixin-moesin homology (FERM) protein domain is a multifunctional protein-lipid binding site, constituting an integral part of numerous membrane-associated proteins. Its interaction with the lipid phosphatidylinositol-4,5-bisphosphate (PIP2), located at the inner leaflet of eukaryotic plasma membranes, is important for localization, anchorage, and activation of FERM-containing proteins. FERM-PIP2 complexes structurally determined so far exclusively feature a 1:1 binding stoichiometry of protein and lipid, with a few basic FERM residues neutralizing the −4 charge of the bound PIP2. Whether this picture from static crystal structures also applies to the dynamic interaction of FERM domains on PIP2 membranes is unknown. We here quantified the stoichiometry of FERM-PIP2 binding in a lipid bilayer using atomistic molecular dynamics simulations and experiments on solid supported membranes for the FERM domains of focal adhesion kinase and ezrin. In contrast to the structural data, we find much higher average stoichiometries of FERM-PIP2 binding, amounting to 1:3 or 1:4 ratios, respectively. In simulations, the full set of basic residues at the membrane interface, 7 and 15 residues for focal adhesion kinase and ezrin, respectively, engages in PIP2 interactions. In addition, Na ions enter the FERM-membrane binding interface, compensating negative PIP2 charges in case of high charge surpluses from bound PIP2. We propose the multivalent binding of FERM domains to PIP2 in lipid bilayers to significantly enhance the stability of FERM-membrane binding and to render the FERM-membrane linkage highly adjustable.

Common framework mutations impact antibody interfacial dynamics and flexibility.

With the flood of engineered antibodies, there is a heightened need to elucidate the structural features of antibodies that contribute to specificity, stability, and breadth. While antibody flexibility and interface angle have begun to be explored, design rules have yet to emerge, as their impact on the metrics above remains unclear. Furthermore, the purpose of framework mutations in mature antibodies is highly convoluted. To this end, a case study utilizing molecular dynamics simulations was undertaken to determine the impact framework mutations have on the VH-VL interface. We further sought to elucidate the governing mechanisms by which changes in the VH-VL interface angle impact structural elements of mature antibodies by looking at root mean squared deviations, root mean squared fluctuations, and solvent accessible surface area. Overall, our results suggest framework mutations can significantly shift the distribution of VH-VL interface angles, which leads to local changes in antibody flexibility through local changes in the solvent accessible surface area. The data presented herein highlights the need to reject the dogma of static antibody crystal structures and exemplifies the dynamic nature of these proteins in solution. Findings from this work further demonstrate the importance of framework mutations on antibody structure and lay the foundation for establishing design principles to create antibodies with increased specificity, stability, and breadth.

Distinct Modes of Hidden Structural Dynamics in the Functioning of an Allosteric Polysaccharide Lyase

Dynamics is an essential process to drive an enzyme to perform a function. When a protein sequence encodes for its three-dimensional structure and hence its function, it essentially defines the intrinsic dynamics of the molecule. The static X-ray crystal structure was thought to shed little insight into the molecule’s dynamics until the recently available tool “Ensemble refinement” (ER). Here, we report the structure–function–dynamics of PanPL, an alginate-specific, endolytic, allosteric polysaccharide lyase belonging to the PL-5 family from Pandoraea apista. The crystal structures determined in apo and tetra-ManA bound forms reveal that the PanPL maintains a closed state with an N-terminal loop lid (N-loop-lid) arched over the active site. The B-factor analyses and ER congruently reveal how pH influences the functionally relevant atomic fluctuations at the N-loop-lid. The ER unveils enhanced fluctuations at the N-loop-lid upon substrate binding. The normal-mode analysis finds that the functional states are confined. The 1 μs simulation study suggests the existence of a hidden open state. The longer N-loop-lid selects a mechanism to adopt a closed state and undergo fluctuations to facilitate the substrate binding. Here, our work demonstrates the distinct modes of dynamics; both intrinsic and substrate-induced conformational changes are vital for enzyme functioning and allostery.

Specific recognition between YTHDF3 and m6 A-modified RNA: An all-atom molecular dynamics simulation study.

The YTH domain of YTHDF3 belongs to a class of protein "readers" recognizing the N6-methyladenosine (m6 A) modification in mRNA. Although static crystal structure reveals m6 A recognition by a conserved aromatic cage, the dynamic process in recognition and importance of aromatic cage residues are not completely clear. Here, molecular dynamics (MD) simulations are performed to explore the issues and negative selectivity of YTHDF3 toward unmethylated substrate. Our results reveal that there exist conformation selectivity and induced-fit in YTHDF3 binding with m6 A-modified RNA, where recognition loop and loop6 play important roles in the specific recognition. m6 A modification enhances the stability of YTHDF3 in complex with RNA. The methyl group of m6 A, like a warhead, enters into the aromatic cage of YTHDF3, where Trp492 anchors the methyl group and constraints m6 A, making m6 A further stabilized by π-π stacking interactions from Trp438 and Trp497. In addition, the methylation enhances the hydrophobicity of adenosine, facilitating water molecules excluded out of the aromatic cage, which is another reason for the specific recognition and stronger intermolecular interaction. Finally, the comparative analyses of hydrogen bonds and binding free energy between the methylated and unmethylated complexes reveal the physical basis for the preferred recognition of m6 A-modified RNA by YTHDF3. This study sheds light on the mechanism by which YTHDF3 specifically recognizes m6 A-modified RNA and can provide important information for structure-based drug design.

Application of Coarse-Grained (CG) Models to Explore Conformational Pathway of Large-Scale Protein Machines.

Protein machines are clusters of protein assemblies that function in order to control the transfer of matter and energy in cells. For a specific protein machine, its working mechanisms are not only determined by the static crystal structures, but also related to the conformational transition dynamics and the corresponding energy profiles. With the rapid development of crystallographic techniques, the spatial scale of resolved structures is reaching up to thousands of residues, and the concomitant conformational changes become more and more complicated, posing a great challenge for computational biology research. Previously, a coarse-grained (CG) model aiming at conformational free energy evaluation was developed and showed excellent ability to reproduce the energy profiles by accurate electrostatic interaction calculations. In this study, we extended the application of the CG model to a series of large-scale protein machine systems. The spike protein trimer of SARS-CoV-2, ATP citrate lyase (ACLY) tetramer, and P4-ATPases systems were carefully studied and discussed as examples. It is indicated that the CG model is effective to depict the energy profiles of the conformational pathway between two endpoint structures, especially for large-scale systems. Both the energy change and energy barrier between endpoint structures provide reasonable mechanism explanations for the associated biological processes, including the opening of receptor binding domain (RBD) of spike protein, the phospholipid transportation of P4-ATPase, and the loop translocation of ACLY. Taken together, the CG model provides a suitable alternative in mechanistic studies related to conformational change in large-scale protein machines.

Solution structure ensemble of human obesity-associated protein FTO reveals druggable surface pockets at the interface between the N- and C-terminal domain

The fat mass and obesity-associated FTO protein catalyzes demethylation of the N6-methyladenosine, an epigenetic mark that controls several metabolic pathways by modulating the transcription, translation, and cellular localization of RNA molecules. Since the discovery that its overexpression links to the development of obesity and cancer, FTO was the target of screening campaigns and structure-based drug design efforts. Although several FTO inhibitors were generated, these often lack potency or selectivity. Herein, we investigate the structure and dynamics of human FTO in solution. We show that the structure of the catalytic N-terminal domain is unstable in the absence of the C-terminal domain, which explains why the isolated N-terminal domain is incompetent for catalysis and suggests that the domain interaction represents a target for the development of specific inhibitors. Then, by using NMR relaxation measurements, we show that the interface between the FTO structural domains, the active site, and several peripheral loops undergo conformational dynamics on both the picosecond–nanosecond and microsecond–millisecond timescales. Consistent with this, we found that the backbone amide residual dipolar couplings measured for FTO in phage pf1 are inconsistent with the static crystal structure of the enzyme. Finally, we generated a conformational ensemble for apo FTO that satisfies the solution NMR data by combining the experimental residual dipolar couplings with accelerated molecular dynamics simulations. Altogether, the structural ensemble reported in this work provides an atomic-resolution model of apo FTO and reveals transient surface pockets at the domain interface that represent potential targets for the design of allosteric inhibitors.

High-speed atomic force microscopy reveals a three-state elevator mechanism in the citrate transporter CitS

The secondary active transporter CitS shuttles citrate across the cytoplasmic membrane of gram-negative bacteria by coupling substrate translocation to the transport of two Na+ ions. Static crystal structures suggest an elevator type of transport mechanism with two states: up and down. However, no dynamic measurements have been performed to substantiate this assumption. Here, we use high-speed atomic force microscopy for real-time visualization of the transport cycle at the level of single transporters. Unexpectedly, instead of a bimodal height distribution for the up and down states, the experiments reveal movements between three distinguishable states, with protrusions of ∼0.5 nm, ∼1.0 nm, and ∼1.6 nm above the membrane, respectively. Furthermore, the real-time measurements show that the individual protomers of the CitS dimer move up and down independently. A three-state elevator model of independently operating protomers resembles the mechanism proposed for the aspartate transporter GltPh Since CitS and GltPh are structurally unrelated, we conclude that the three-state elevators have evolved independently.

NKG2D discriminates diverse ligands through selectively mechano‐regulated ligand conformational changes

Stimulatory immune receptor NKG2D binds diverse ligands to elicit differential anti‐tumor and anti‐virus immune responses. Two conflicting degeneracy recognition models based on static crystal structures and in‐solution binding affinities have been considered for almost two decades. Whether and how NKG2D recognizes and discriminates diverse ligands still remain unclear. Using live‐cell‐based single‐molecule biomechanical assay, we characterized the in situ binding kinetics of NKG2D interacting with different ligands in the absence or presence of mechanical force. We found that mechanical force application selectively prolonged NKG2D interaction lifetimes with the ligands MICA and MICB, but not with ULBPs, and that force‐strengthened binding is much more pronounced for MICA than for other ligands. We also integrated steered molecular dynamics simulations and mutagenesis to reveal force‐induced rotational conformational changes of MICA, involving formation of additional hydrogen bonds on its binding interface with NKG2D, impeding MICA dissociation under force. We further provided a kinetic triggering model to reveal that force‐dependent affinity determines NKG2D ligand discrimination and its downstream NK cell activation. Together, our results demonstrate that NKG2D has a discrimination power to recognize different ligands, which depends on selective mechanical force‐induced ligand conformational changes.

Computational Alanine Scanning Reveals Common Features of TCR/pMHC Recognition in HLA-DQ8-Associated Celiac Disease.

In HLA-DQ8-associated celiac disease, Gliadin-γ1 or Gliadin-α1 peptide is presented to the cell surface and recognized by several types of T-cell receptor (TCR), but it is still unclear how the TCR, peptide, and the major histocompatibility complex (MHC) act together to trigger celiac disease. For now, most of the analysis is based on static crystal structures. And the detailed information about these structures based on energetic interaction is still lacking. Here, we took four types of celiac disease-related MHC-peptide-TCR structures from three patients to perform computational alanine scanning calculations using the molecular mechanics generalized born surface area (MM/GBSA) approach combined with a recently developed interaction entropy (IE) method to identify the key residues on TCR, peptide, and MHC. Our study aims to shed some light on the interaction mechanism of this complex protein interaction system. Based on detailed computational analysis and mutational calculations, important binding interactions in these triple-interaction complexes are analyzed, and critical residues responsible for TCR/pMHC recognition pattern in HLA-DQ8-associated celiac disease are presented. These detailed analysis and computational result should help shed light on our understanding of the celiac disease and the development of the medical treatment.

Spin-crossover materials: Getting the most from x-ray crystallography

The physical phenomenon of spin-crossover in molecular crystals is a multiscale process whose properties rely on the supramolecular organization of the spin-crossover active elements, their interactions within the crystal packing, and their dynamics. The delicate balance between short-range and long-range structural reorganizations upon the spin transition is at the origin of remarkable and fascinating physical phenomena such as thermal, light-induced and pressure-induced hysteresis, multi-step transitions, or multimetastablility. A complete understanding of the various phenomena associated with spin-crossover requires a comprehensive and thorough characterization of the overall structural architecture at all scales, which goes beyond the average static crystal structure. This Tutorial surveys the practical use of x-ray crystallography notably in non-ambient conditions to provide a direct view of the physical processes operating in spin-crossover molecular solids from bulk single crystals to nanocrystalline powder. Advanced x-ray crystallography methods are reviewed and illustrated with a series of model examples.

Membrane Environment Modulates Ligand-Binding Propensity of P2Y12 Receptor.

The binding of natural ligands and synthetic drugs to the P2Y12 receptor is of great interest because of its crucial role in platelets activation and the therapy of arterial thrombosis. Up to now, all computational studies of P2Y12 concentrated on the available crystal structures, while the role of intrinsic protein dynamics and the membrane environment in the functioning of P2Y12 was not clear. In this work, we performed all-atom molecular dynamics simulations of the full-length P2Y12 receptor in three different membrane environments and in two possible conformations derived from available crystal structures. The binding of ticagrelor, its two major metabolites, adenosine diphosphate (ADP) and 2-Methylthioadenosine diphosphate (2MeS-ADP) as agonist, and ethyl 6-[4-(benzylsulfonylcarbamoyl)piperidin-1-yl]-5-cyano-2-methylpyridine-3-carboxylate (AZD1283)as antagonist were assessed systematically by means of ensemble docking. It is shown that the binding of all ligands becomes systematically stronger with the increase of the membrane rigidity. Binding of all ligands to the agonist-bound-like conformations is systematically stronger in comparison to antagonist-bound-likes ones. This is dramatically opposite to the results obtained for static crystal structures. Our results show that accounting for internal protein dynamics, strongly modulated by its lipid environment, is crucial for correct assessment of the ligand binding to P2Y12.

Microsecond molecular dynamics suggest that a non-synonymous mutation, frequently observed in patients with mild symptoms in Tokyo, alters dynamics of the SARS-CoV-2 main protease.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), which causes the coronavirus disease 2019 (COVID-19), spread rapidly around the globe. The main protease encoded by SARS-CoV-2 is essential for processing of the polyproteins translated from the viral RNA genome, making this protein a potential drug target. A recently reported mutation in the protease, P108S, may be responsible for milder symptoms observed in COVID-19 patients in Tokyo. Starting from a crystal structure of the SARS-CoV-2 main protease in the dimeric form, we performed triplicate 5.0-μs molecular dynamics simulations of the wild-type and P108S mutant. Our computational results suggest a link between the mutation P108S and dynamics of the catalytic sites in the main protease: The catalytic dyad become considerably inaccessible to substrates in the P108S mutant. Our results also demonstrate the potential of molecular dynamics simulations to complement experimental techniques and other computational methods, such as protein design calculations, which predict effects of mutations based on static crystal structures. Further studies are certainly necessary to quantitively understand the relationships between the P108S mutation and physical properties of the main protease, but the results of our study will immediately inform development of new protease inhibitors.

Exploring cooperative porosity in organic cage crystals using in situ diffraction and molecular simulations.

A porous organic cage crystal, α-CC2, shows unexpected adsorption of sulphur hexafluoride (SF6) in its cage cavities: analysis of the static crystal structure indicates that SF6 is occluded, as even the smallest diatomic gas, H2, is larger than the window of the cage pore. Herein, we use in situ powder X-ray diffraction (PXRD) experiments to provide unequivocal evidence for the presence of SF6 inside the 'occluded' cage voids, pointing to a mechanism of dynamic flexibility of the system. By combining PXRD results with molecular dynamics simulations, we build a molecular level picture of the cooperative porosity in α-CC2 that facilitates the passage of SF6 into the cage voids.

Druggability Assessment for Selected Serine Proteases in a Pharmaceutical Industry Setting.

Target druggability assessment is an integral part of the early target characterization and selection process in pharmaceutical industry. Here, we investigate a set of five different serine proteases from the blood coagulation cascade. The aim of this study is twofold. Firstly, leveraging the wealth of available in-house high-throughput screening (HTS) data, we analyze HTS hit rates and discuss their predictive value for the development of small molecule (SMOL) candidates. Purely structure-activity relationship (SAR) based druggability ratings are compared with computational protein-structure based druggability assessments. Secondly, we evaluate the impact of using conformational ensembles from molecular dynamics (MD) simulations instead of single static crystal structures as basis for computational druggability assessments. Based on this study, we recommend incorporating molecular dynamics routinely into the early target characterization process, especially if only a single X-ray structure is available.

Elucidating the atomistic origin of anharmonicity in tetragonal CH3NH3PbI3 with Raman scattering

Halide perovskite (HP) semiconductors exhibit unique strong coupling between the electronic and structural dynamics. The high-temperature cubic phase of HPs is known to be entropically stabilized, with imaginary frequencies in the calculated phonon dispersion relation. Similar calculations, based on the static average crystal structure, predict a stable tetragonal phase with no imaginary modes. This work shows that in contrast to standard theory predictions, the room-temperature tetragonal phase of CH$_{3} $NH$_{3} $PbI$_{3}$ is strongly anharmonic. We use Raman polarization-orientation (PO) measurements and \textit{ab initio} molecular dynamics (AIMD) to investigate the origin and temperature evolution of the strong structural anharmonicity throughout the tetragonal phase. Raman PO measurements reveal a new spectral feature that resembles a soft mode. This mode shows an unusual continuous increase in damping with temperature which is indicative of an anharmonic potential surface. The analysis of AIMD trajectories identifies two major sources of anharmonicity: the orientational unlocking of the [CH$_{3} $NH$_{3}$]$^+$ ions and large amplitude octahedral tilting that continuously increases with temperature. Our work suggests that the standard phonon picture cannot describe the structural dynamics of tetragonal CH$_{3} $NH$_{3} $PbI$_{3}$.

Residue interaction dynamics in Vaucheria aureochrome1 light-oxygen-voltage: Bridging theory and experiments.

Allosteric communication is the basis of signaling and information transfer. Collective interactions between amino acid residues, which are spatially distributed in the three dimensional structure of a protein molecule, form the basis of allosteric network. While the construction of residue interaction graphs (RIG) is based on static crystal structures of proteins, it is important to extract information on protein dynamics to understand allostery. Therefore, quantitative analysis of RIG based on the framework of differential network (DN), is immensely helpful in identifying key amino acid residue interactions within such communication pathways. While the simultaneous availability of protein structures from two different states is essential for DN, there are additional challenges. Crystallographic artifacts like nonbiological dimeric arrangements within the crystal lattice automatically influence the construction and eventually the interpretation of RIG. Therefore, experimental validation of predictions from the analyses of RIG is naturally scarce in the literature. Herein, we study the photo sensor domain of the signaling photoreceptor transcription factor, aureochrome1, to understand light-driven signaling. We perform direct experiments to verify the predictions from RIG using the machinery of DN. However, the agreement leaves scope for improvement. We then discuss the notion of quaternary structure alignment to obtain a biologically meaningful dimer. Thence, we reconstruct the RIG and reanalyze the modified structure. Results of these reanalyses render far superior agreement with experiments. Therefore, this notion of addressing crystallographic biases provides a fresh yet general approach for reconciliation of theory and experiments. It is applicable beyond the present case to all signaling proteins in general.