Sampling of slow diffusive conformational transitions with accelerated molecular dynamics

Exploring biased activation characteristics by molecular dynamics simulation and machine learning for the μ-opioid receptor

Biased ligands selectively activating specific downstream signaling pathways (termed as biased activation) exhibit significant therapeutic potential. However, the conformational characteristics revealed are very limited for the biased activation, which is not conducive to biased drug development. Motivated by the issue, we combine extensive accelerated molecular dynamics simulations and an interpretable deep learning model to probe the biased activation features for two complex systems constructed by the inactive μOR and two different biased agonists (G-protein-biased agonist TRV130 and β-arrestin-biased agonist endomorphin2). The results indicate that TRV130 binds deeper into the receptor core compared to endomorphin2, located between W2936.48 and D1142.50, and forms hydrogen bonding with D1142.50, while endomorphin2 binds above W2936.48. The G protein-biased agonist induces greater outward movements of the TM6 intracellular end, forming a typical active conformation, while the β-arrestin-biased agonist leads to a smaller extent of outward movements of TM6. Compared with TRV130, endomorphin2 causes more pronounced inward movements of the TM7 intracellular end and more complex conformational changes of H8 and ICL1. In addition, important residues determining the two different biased activation states were further identified by using an interpretable deep learning classification model, including some common biased activation residues across Class A GPCRs like some key residues on the TM2 extracellular end, ECL2, TM5 intracellular end, TM6 intracellular end, and TM7 intracellular end, and some specific important residues of ICL3 for μOR. The observations will provide valuable information for understanding the biased activation mechanism for GPCRs.

Flanking Domains Modulate α-Synuclein Monomer Structure: A Molecular Dynamics Domain Deletion Study

Aggregates of misfolded α-synuclein proteins (asyn) are key markers of Parkinson's disease. Asyn proteins have three domains: an N-terminal domain, a hydrophobic NAC core implicated in aggregation, and a proline-rich C-terminal domain. Proteins with truncated C-terminal domains are known to be prone to aggregation and suggest that studying domain-domain interactions in asyn monomers could help elucidate the role of the flanking domains in modulating protein structure. To this end, we used Gaussian accelerated molecular dynamics (GAMD) to simulate wild-type (WT), N-terminal truncated (DN), C-terminal truncated (ΔC), and isolated NAC domain variants (isoNAC). Using clustering and contact analysis, we found that N- and C-terminal domains interact via electrostatic interactions, while the NAC and N-terminal domains interact through hydrophobic contacts. Our work also suggests that the C-terminal domain does not interact directly with the NAC domain but instead interacts with the N-terminal domain. Removal of the N-terminal domain led to increased contacts between NAC and C-terminal domains and the formation of interdomain β-sheets. Removal of either flanking domain also resulted in increased compactness of every domain. We also found that the contacts between flanking domains results in an electrostatic potential (ESP) that could possibly lead to favorable interactions with anionic lipid membranes. Removal of the C-terminal domain disrupts the ESP in a way that is likely to over-stabilize protein-membrane interactions. All of this suggests that one of the roles of the flanking domains may be to modulate the protein structure in a way that helps maintain elongation, hide hydrophobic residue from the solvent, and maintain an ESP that aids favorable interactions with the membrane.

Rarγ -Foxa1 signaling promotes luminal identity in prostate progenitors and is disrupted in prostate cancer

Retinoic acid (RA) signaling is a master regulator of vertebrate development with crucial roles in directing body axis orientation and tissue differentiation, including in the reproductive system. However, a mechanistic understanding of how RA signaling promotes cell lineage identity in different tissues is often missing. Here, leveraging prostate organoid technology, we demonstrated that RA signaling orchestrates the commitment of adult mouse prostate progenitors to glandular identity, epithelial barrier integrity, and ultimately, proper specification of the prostatic lumen. Mechanistically, RA-dependent RARγ activation promotes the expression of the pioneer factor Foxa1, which synergizes with the androgen pathway for proper luminal expansion, cytoarchitecture and function. FOXA1 nucleotide variants are common in human prostate and breast cancers and considered driver mutations, though their pathogenic mechanism is incompletely understood. Combining functional genetics experiments with structural modeling of FOXA1 folding and chromatin binding analyses, we discovered that FOXA1 F254E255 is a loss-of-function mutation leading to compromised transcriptional function and lack of luminal fate commitment of prostate progenitors. Overall, we define RA as a crucial instructive signal for glandular identity in adult prostate progenitors. We propose deregulation of vitamin A metabolism as a risk factor for benign and malignant prostate disease, and identified cancer associated FOXA1 indels affecting residue F254 as loss-of-function mutations promoting dedifferentiation of adult prostate progenitors. Summary: Retinoic acid signaling orchestrates luminal differentiation of adult prostate progenitors.

Exploring the DNA2-PNA heterotriplex formation in targeting the Bcl-2 gene promoter: A structural insight by physico-chemical and microsecond-scale MD investigation

Peptide Nucleic Acids (PNAs) represent a promising tool for gene modulation in anticancer treatment. The uncharged peptidyl backbone and the resistance to chemical and enzymatic degradation make PNAs highly advantageous to form stable hybrid complexes with complementary DNA and RNA strands, providing higher stability than the corresponding natural analogues. Our and other groups' research has successfully shown that tailored PNA sequences can effectively downregulate the expression of human oncogenes using antigene, antisense, or anti-miRNA approaches. Specifically, we identified a seven bases-long PNA sequence, complementary to the longer loop of the main G-quadruplex structure formed by the bcl2midG4 promoter sequence, capable of downregulating the expression of the antiapoptotic Bcl-2 protein and enhancing the anticancer activity of an oncolytic adenovirus. Here, we extended the length of the PNA probe with the aim of including the double-stranded Bcl-2 promoter among the targets of the PNA probe. Our investigation primarily focused on the structural aspects of the resulting DNA2-PNA heterotriplex that were determined by employing conventional and accelerated microsecond-scale molecular dynamics simulations and chemical-physical analysis. Additionally, we conducted preliminary biological experiments using cytotoxicity assays on human A549 and MDA-MB-436 adenocarcinoma cell lines, employing the oncolytic adenovirus delivery strategy.

Expanding the DNA editing toolbox: Novel lambda integrase variants targeting microalgal and human genome sequences

Recombinase enzymes are extremely efficient at integrating very large DNA fragments into target genomes. However, intrinsic sequence specificities curtail their use to DNA sequences with sufficient homology to endogenous target motifs. Extensive engineering is therefore required to broaden applicability and robustness. Here, we describe the directed evolution of novel lambda integrase variants capable of editing exogenous target sequences identified in the diatom Phaeodactylum tricornutum and the algae Nannochloropsis oceanica. These microorganisms hold great promise as conduits for green biomanufacturing and carbon sequestration. The evolved enzyme variants show >1000-fold switch in specificity towards the non-natural target sites when assayed in vitro. A single-copy target motif in the human genome with homology to the Nannochloropsis oceanica site can also be efficiently targeted using an engineered integrase, both in vitro and in human cells. The developed integrase variants represent useful additions to the DNA editing toolbox, with particular application for targeted genomic insertion of large DNA cargos.

OpenMM 8: Molecular Dynamics Simulation with Machine Learning Potentials

Machine learning plays an important and growing role in molecular simulation. The newest version of the OpenMM molecular dynamics toolkit introduces new features to support the use of machine learning potentials. Arbitrary PyTorch models can be added to a simulation and used to compute forces and energy. A higher-level interface allows users to easily model their molecules of interest with general purpose, pretrained potential functions. A collection of optimized CUDA kernels and custom PyTorch operations greatly improves the speed of simulations. We demonstrate these features in simulations of cyclin-dependent kinase 8 (CDK8) and the green fluorescent protein chromophore in water. Taken together, these features make it practical to use machine learning to improve the accuracy of simulations with only a modest increase in cost.

Roles of Accelerated Molecular Dynamics Simulations in Predictions of Binding Kinetic Parameters

Rational predictions on binding kinetics parameters of drugs to targets play significant roles in future drug designs. Full conformational samplings of targets are requisite for accurate predictions of binding kinetic parameters. In this review, we mainly focus on the applications of enhanced sampling technologies in calculations of binding kinetics parameters and residence time of drugs. The methods involved in molecular dynamics simulations are applied to not only probe conformational changes of targets but also reveal calculations of residence time that is significant for drug efficiency. For this review, special attention are paid to accelerated molecular dynamics (aMD) and Gaussian aMD (GaMD) simulations that have been adopted to predict the association or disassociation rate constant. We also expect that this review can provide useful information for future drug design.

Accelerated molecular dynamics study to compare the thermostability of Bacillus licheniformis and Aspergillus niger α-amylase

The thermostability of enzymes plays a significant role in the starch hydrolysis process in the industry. The structural difference between thermostable Bacillus licheniformis α-amylase (BLA) and thermolabile Aspergillus niger α-amylase (ANA) is interesting to be explored. This work aimed to study the thermostability-determining factor of BLA as compared to a non-thermostable enzyme, ANA, using molecular dynamics (MD) simulation at a high temperature. A 100 ns of classical MD, which was followed by 200 ns accelerated MD was conducted to explore the conformational changes of the enzyme. It is revealed that the intramolecular interactions through salt bridge interactions and the presence of calcium ions dominates the stability effect of BLA, despite the absence of a disulfide bond in the structure. These results should be useful in designing a thermostable enzyme that can be used in industrial processes.Communicated by Ramaswamy H. Sarma.

Extended Ensemble Molecular Dynamics Study of Ammonia-Cellulose I Complex Crystal Models: Free-Energy Landscape and Atomistic Pictures of Ammonia Diffusion in the Crystalline Phase

Here, we report extended ensemble molecular dynamics simulations of ammonia-cellulose I complex crystal models to evaluate the diffusion behavior of the guest ammonia molecules and the potential of mean force (PMF), namely, the free energy change along the chosen reaction coordinate, for migration of an ammonia molecule in the crystal models. Accelerated molecular dynamics simulations confirmed that ammonia molecules almost exclusively diffused through the hydrophilic channel even when the crystal framework was retained. Adaptive steered molecular dynamics simulations detected distinct PMF peaks with heights of approximately 7 kcal/mol as the ammonia molecule passed through the cellulose-chain layers. Introducing hybrid quantum mechanical and molecular mechanics theory to the adaptive steered molecular dynamics simulation effectively lowered the heights of the PMF peaks to approximately 5 kcal/mol, accompanied by a slight decrease in the baseline. Removal of the ammonia molecules in the neighboring channels resulted in a continuous increase in the baseline for the migration of an ammonia molecule in the hydrophilic channel. When the halves of the crystal model were separated to widen the hydrophilic channel to 0.2 nm, the PMF profiles exhibited an unexpected increase. This resulted from water structuring in the expanded hydrophilic channel, which disappeared with further expansion of the hydrophilic channel to 0.3 nm.

Thermostabilizing mechanisms of canonical single amino acid substitutions at a GH1 β-glucosidase probed by multiple MD and computational approaches

β-glucosidases play a pivotal role in second-generation biofuel (2G-biofuel) production. For this application, thermostable enzymes are essential due to the denaturing conditions on the bioreactors. Random amino acid substitutions have originated new thermostable β-glucosidases, but without a clear understanding of their molecular mechanisms. Here, we probe by different molecular dynamics simulation approaches with distinct force fields and submitting the results to various computational analyses, the molecular bases of the thermostabilization of the Paenibacillus polymyxa GH1 β-glucosidase by two-point mutations E96K (TR1) and M416I (TR2). Equilibrium molecular dynamic simulations (eMD) at different temperatures, principal component analysis (PCA), virtual docking, metadynamics (MetaDy), accelerated molecular dynamics (aMD), Poisson-Boltzmann surface analysis, grid inhomogeneous solvation theory and colony method estimation of conformational entropy allow to converge to the idea that the stabilization carried by both substitutions depend on different contributions of three classic mechanisms: (i) electrostatic surface stabilization; (ii) efficient isolation of the hydrophobic core from the solvent, with energetic advantages at the solvation cap; (iii) higher distribution of the protein dynamics at the mobile active site loops than at the protein core, with functional and entropic advantages. Mechanisms i and ii predominate for TR1, while in TR2, mechanism iii is dominant. Loop A integrity and loops A, C, D, and E dynamics play critical roles in such mechanisms. Comparison of the dynamic and topological changes observed between the thermostable mutants and the wildtype protein with amino acid co-evolutive networks and thermostabilizing hotspots from the literature allow inferring that the mechanisms here recovered can be related to the thermostability obtained by different substitutions along the whole family GH1. We hope the results and insights discussed here can be helpful for future rational approaches to the engineering of optimized β-glucosidases for 2G-biofuel production for industry, biotechnology, and science.

Role of Thylakoid Lipids in Protochlorophyllide Oxidoreductase Activation: Allosteric Mechanism Elucidated by a Computational Study

Light-dependent protochlorophyllide oxidoreductase (LPOR) is a chlorophyll synthetase that catalyzes the reduction of protochlorophyllide (Pchlide) to chlorophyllide (Chlide) with indispensable roles in regulating photosynthesis processes. A recent study confirmed that thylakoid lipids (TL) were able to allosterically enhance modulator-induced LPOR activation. However, the allosteric modulation mechanism of LPOR by these compounds remains unclear. Herein, we integrated multiple computational approaches to explore the potential cavities in the Arabidopsis thaliana LPOR and an allosteric site around the helix-G region where high affinity for phosphatidyl glycerol (PG) was identified. Adopting accelerated molecular dynamics simulation for different LPOR states, we rigorously analyzed binary LPOR/PG and ternary LPOR/NADPH/PG complexes in terms of their dynamics, energetics, and attainable allosteric regulation. Our findings clarify the experimental observation of increased NADPH binding affinity for LPOR with PGs. Moreover, the simulations indicated that allosteric regulators targeting LPOR favor a mechanism involving lid opening upon binding to an allosteric hinge pocket mechanism. This understanding paves the way for designing novel LPOR activators and expanding the applications of LPOR.

Synthesis, In Vitro Profiling, and In Vivo Evaluation of Benzohomoadamantane-Based Ureas for Visceral Pain: A New Indication for Soluble Epoxide Hydrolase Inhibitors

The soluble epoxide hydrolase (sEH) has been suggested as a pharmacological target for the treatment of several diseases, including pain-related disorders. Herein, we report further medicinal chemistry around new benzohomoadamantane-based sEH inhibitors (sEHI) in order to improve the drug metabolism and pharmacokinetics properties of a previous hit. After an extensive in vitro screening cascade, molecular modeling, and in vivo pharmacokinetics studies, two candidates were evaluated in vivo in a murine model of capsaicin-induced allodynia. The two compounds showed an anti-allodynic effect in a dose-dependent manner. Moreover, the most potent compound presented robust analgesic efficacy in the cyclophosphamide-induced murine model of cystitis, a well-established model of visceral pain. Overall, these results suggest painful bladder syndrome as a new possible indication for sEHI, opening a new range of applications for them in the visceral pain field.

Encapsulation Enhances the Catalytic Activity of C-N Coupling: Reaction Mechanism of a Cu(I)/Calix[8]arene Supramolecular Catalyst

Development of C-N coupling methodologies based on Earth-abundant metals is a promising strategy in homogeneous catalysis for sustainable processes. However, such systems suffer from deactivation and low catalytic activity. We here report that encapsulation of Cu(I) within the phenanthroyl-containing calix[8]arene derivative 1,5-(2,9-dimethyl-1,10-phenanthroyl)-2,3,4,6,7,8-hexamethyl-p-tert-butylcalix[8]arene (C8PhenMe6 ) significantly enhances C-N coupling activity up to 92 % yield in the reaction of aryl halides and aryl amines, with low catalyst loadings (2.5 % mol). A tailored multiscale computational protocol based on Molecular Dynamics simulations and DFT investigations revealed an oxidative addition/reductive elimination process of the supramolecular catalyst [Cu(C8PhenMe6)I]. The computational investigations uncovered the origins of the enhanced catalytic activity over its molecular analogues: Catalyst deactivation through dimerization is prevented, and product release facilitated. Capturing the dynamic profile of the macrocycle and the impact of non-covalent interactions on reactivity allows for the rationalization of the behavior of the flexible supramolecular catalysts employed.

Recognition between CD147 and cyclophilin A deciphered by accelerated molecular dynamics simulations

CD147 functions as the receptor of extracellular cyclophilin A (CypA) in various diseases, and CD147-CypA binding ulteriorly underlies the pathological process of various viral infections including HIV-1, SARS, and SARS-CoV-2. Although CyPA has been identified as a key intermediate pro-inflammatory factor, the mechanism by which CD147 cooperates with CypA in the development of the cytokine storm remains largely unknown, and the binding profile of CD147 with CypA remains to be elucidated as well. Here, we prepared three binding models of the CD147-CypA complex, including the active site of CypA severally binding to the groove bound by the Ig1 and Ig2 domains (model-0), P180-G181 (model-1), and P211 (model-2) of CD147, as well as introducing mutations P180A-G181A and P211A individually in each model. All systems were studied using accelerated molecular dynamics simulations and the molecular mechanics generalized Born surface area (MM/GBSA) method. For model-0, CypA bound to the ectodomain of CD147 with the highest binding affinity. Moreover, mutations P180A-G181A of CD147 in model-0 decreased the binding affinity and weakened the dynamic correlation between CD147 and CypA, which resulted in CypA shifting from the initial binding location. Other residue mutations of CD147 did not significantly affect the CD147-CypA binding, as reflected by the energy and structural analyses. Compared with surface plasmon resonance results and nuclear magnetic resonance shift signals, CypA should tend to reciprocally bind to the groove of CD147, and the binding process might be modulated by P180-G181 rather than P211. Besides, residue R201 of CD147 is critical for CD147-CypA binding and needs further experimental verification. These findings further our understanding of the recruitment between CD147 and CypA and its potential role in the development of inflammation and viral infection.

Implementing accelerated dynamics to unravel the effects of high-fidelity Cas9 mutants on target DNA and guide RNA hybrid stability

The clustered regularly interspersed short palindromic repeats (CRISPR) and its associated nuclease (Cas9) offers a unique and easily reprogrammable system for editing eukaryotic genomes. Cas9 is guided to the target by an RNA strand, and precise edits are created by introducing double-stranded breaks. However, nuclease activity of Cas9 is also triggered at other sites other than the target sit, which is a major limitation for various applications. Cas9 variants have been designed to improve the efficacy of the tool by introducing certain mutations. However, the on-target activity of such Cas9 variants is often seen as compromised. Hence, understanding the sub-molecular differences in the variants is essential to elucidate the factors that contribute to efficiency. The study reveals distortions in the PAM-distal regions of the nucleic hybrids as well as changes in the interactions between the Cas9 variants and RNA-DNA hybrid, contributing to the explanation for differences in on-target activity.Communicated by Ramaswamy H. Sarma.

Improving the Accuracy of Atomistic Simulations of the Electrochemical Interface

Atomistic simulation of the electrochemical double layer is an ambitious undertaking, requiring quantum mechanical description of electrons, phase space sampling of liquid electrolytes, and equilibration of electrolytes over nanosecond time scales. All models of electrochemistry make different trade-offs in the approximation of electrons and atomic configurations, from the extremes of classical molecular dynamics of a complete interface with point-charge atoms to correlated electronic structure methods of a single electrode configuration with no dynamics or electrolyte. Here, we review the spectrum of simulation techniques suitable for electrochemistry, focusing on the key approximations and accuracy considerations for each technique. We discuss promising approaches, such as enhanced sampling techniques for atomic configurations and computationally efficient beyond density functional theory (DFT) electronic methods, that will push electrochemical simulations beyond the present frontier.

TAB1 binding induced p38α conformation change: an accelerated molecular dynamics simulation study

p38α mitogen-activated protein kinase (MAPK) undergoes autophosphorylation induced by the binding of TGFβ-activated kinase 1 binding protein 1 (TAB1) in myocardial ischemia. Investigation of the conformational transformations in p38α triggered by TAB1 binding is motivated by the need to find selective p38α activation inhibitors to treat myocardial ischemia. Herein, the conformational transformations of p38α were studied via all-atom accelerated molecular dynamics simulations and principal component analysis. With the binding of TAB1, the conformational changes of p38α auto-activation were characterized by the movement of the activation loop (A-loop) away from the αG helix toward the αF, αE helixes and L16-loop. In addition, a diverse intermediate state with an extensional and phosphorylated A-loop different from the transition intermediate state was explored. The conformational changes, including the A-loop alpha-structure breaking and the stronger hydrogen bond network formation, are accompanied by the extension of the A-loop and more intramolecular interactions in p38α. TAB1 correlates with other regions of p38α that are distal from the TAB1-binding site, including the A-loop, αC helix, and L16-loop, which regulates the intramolecular correlation of p38α. And, the phosphorylation further enhances the correlations between the A-loop and the other regions of p38α. The correlation results imply the regulation process of p38α conformational transformations. These findings will improve our understanding of the autophosphorylation of kinase and facilitate the development of selective inhibitors for the treatment of ischemic injury.

Time Evolution of the Millisecond Allosteric Activation of Imidazole Glycerol Phosphate Synthase

Deciphering the molecular mechanisms of enzymatic allosteric regulation requires the structural characterization of functional states and also their time evolution toward the formation of the allosterically activated ternary complex. The transient nature and usually slow millisecond time scale interconversion between these functional states hamper their experimental and computational characterization. Here, we combine extensive molecular dynamics simulations, enhanced sampling techniques, and dynamical networks to describe the allosteric activation of imidazole glycerol phosphate synthase (IGPS) from the substrate-free form to the active ternary complex. IGPS is a heterodimeric bienzyme complex whose HisH subunit is responsible for hydrolyzing glutamine and delivering ammonia for the cyclase activity in HisF. Despite significant advances in understanding the underlying allosteric mechanism, essential molecular details of the long-range millisecond allosteric activation of IGPS remain hidden. Without using a priori information of the active state, our simulations uncover how IGPS, with the allosteric effector bound in HisF, spontaneously captures glutamine in a catalytically inactive HisH conformation, subsequently attains a closed HisF:HisH interface, and finally forms the oxyanion hole in HisH for efficient glutamine hydrolysis. We show that the combined effector and substrate binding dramatically decreases the conformational barrier associated with oxyanion hole formation, in line with the experimentally observed 4500-fold activity increase in glutamine hydrolysis. The allosteric activation is controlled by correlated time-evolving dynamic networks connecting the effector and substrate binding sites. This computational strategy tailored to describe millisecond events can be used to rationalize the effect of mutations on the allosteric regulation and guide IGPS engineering efforts.

GLOW: A Workflow Integrating Gaussian-Accelerated Molecular Dynamics and Deep Learning for Free Energy Profiling

We introduce a Gaussian-accelerated molecular dynamics (GaMD), deep learning (DL), and free energy profiling workflow (GLOW) to predict molecular determinants and map free energy landscapes of biomolecules. All-atom GaMD-enhanced sampling simulations are first performed on biomolecules of interest. Structural contact maps are then calculated from GaMD simulation frames and transformed into images for building DL models using a convolutional neural network. Important structural contacts are further determined from DL models of attention maps of the structural contact gradients, which allow us to identify the system reaction coordinates. Finally, free energy profiles are calculated for the selected reaction coordinates through energetic reweighting of the GaMD simulations. We have also successfully demonstrated GLOW for the characterization of activation and allosteric modulation of a G protein-coupled receptor, using the adenosine A₁ receptor (A₁AR) as a model system. GLOW findings are highly consistent with previous experimental and computational studies of the A₁AR, while also providing further mechanistic insights into the receptor function. In summary, GLOW provides a systematic approach to mapping free energy landscapes of biomolecules. The GLOW workflow and its user manual can be downloaded at http://miaolab.org/GLOW.

Molecular insights into the allosteric coupling mechanism between an agonist and two different transducers for μ-opioid receptors

G protein-coupled receptors (GPCRs) as the most important class of pharmacological targets regulate G-protein and β-arrestin-mediated signaling through allosteric interplay, which are responsible for different biochemical and physiological actions like therapeutic efficacy and side effects. However, the allosteric mechanism underlying preferentially recruiting one transducer versus the other has been poorly understood, limiting drug design. Motivated by this issue, we utilize accelerated molecular dynamics simulation coupled with potential of mean force (PMF), molecular mechanics Poisson Boltzmann surface area (MM/PBSA) and protein structure network (PSN) to study two ternary complex systems of a representative class A GPCR (μ-opioid receptor (μOR)) bound by an agonist and one specific transducer (G-protein and β-arrestin). The results show that no significant difference exists in the whole structure of μOR between two transducer couplings, but displays transducer-dependent changes in the intracellular binding region of μOR, where the β-arrestin coupling results in a narrower crevice with TM7 inward movement compared with the G-protein. In addition, both the G-protein and β-arrestin coupling can increase the binding affinity of the agonist to the receptor. However, the interactions between the agonist and μOR also exhibit transducer-specific changes, in particular for the interaction with ECL2 that plays an important role in recruiting β-arrestin. The allosteric network analysis further indicates that Y148^3.33, F152^3.37, F156^3.41, N191^4.49, T160^3.45, Y106^2.42, W293^6.48, F289^6.44, I248^5.54 and Y252^5.58 play important roles in equally activating G-protein and β-arrestin. In contrast, M161^3.46 and R165^3.50 devote important contributions to preferentially recruit G-protein while D164^3.49 and R179^ICL2 are revealed to be important for selectively activating β-arrestin. The observations provide useful information for understanding the biased activation mechanism.

Accelerated Ligand-Mapping Molecular Dynamics Simulations for the Detection of Recalcitrant Cryptic Pockets and Occluded Binding Sites

The identification and characterization of binding sites is a critical component of structure-based drug design (SBDD). Probe-based/cosolvent molecular dynamics (MD) methods that allow for protein flexibility have been developed to predict ligand binding sites. However, cryptic pockets that appear only upon ligand binding and occluded binding sites with no access to the solvent pose significant challenges to these methods. Here, we report the development of accelerated ligand-mapping MD (aLMMD), which combines accelerated MD with LMMD, for the detection of these challenging binding sites. The method was validated on five proteins with what we term "recalcitrant" cryptic pockets, which are deeply buried pockets that require extensive movement of the protein backbone to expose, and three proteins with occluded binding sites. In all the cases, aLMMD was able to detect and sample the binding sites. Our results suggest that aLMMD could be used as a general approach for the detection of such elusive binding sites in protein targets, thus providing valuable information for SBDD.

Enhanced sampling without borders: on global biasing functions and how to reweight them

Molecular dynamics (MD) simulations are a powerful tool to follow the time evolution of biomolecular motions in atomistic resolution. However, the high computational demand of these simulations limits the timescales of motions that can be observed. To resolve this issue, so called enhanced sampling techniques are developed, which extend conventional MD algorithms to speed up the simulation process. Here, we focus on techniques that apply global biasing functions. We provide a broad overview of established enhanced sampling methods and promising new advances. As the ultimate goal is to retrieve unbiased information from biased ensembles, we also discuss benefits and limitations of common reweighting schemes. In addition to concisely summarizing critical assumptions and implications, we highlight the general application opportunities as well as uncertainties of global enhanced sampling.

Binding Analysis Using Accelerated Molecular Dynamics Simulations and Future Perspectives

Biomolecular recognition such as binding of small molecules, nucleic acids, peptides and proteins to their target receptors plays key roles in cellular function and has been targeted for therapeutic drug design. Molecular dynamics (MD) is a computational approach to analyze these binding processes at an atomistic level, which provides valuable understandings of the mechanisms of biomolecular recognition. However, the rather slow biomolecular binding events often present challenges for conventional MD (cMD), due to limited simulation timescales (typically over hundreds of nanoseconds to tens of microseconds). In this regard, enhanced sampling methods, particularly accelerated MD (aMD), have proven useful to bridge the gap and enable all-atom simulations of biomolecular binding events. Here, we will review the recent method developments of Gaussian aMD (GaMD), ligand GaMD (LiGaMD) and peptide GaMD (Pep-GaMD), which have greatly expanded our capabilities to simulate biomolecular binding processes. Spontaneous binding of various biomolecules to their receptors has been successfully simulated by GaMD. Microsecond LiGaMD and Pep-GaMD simulations have captured repetitive binding and dissociation of small-molecule ligands and highly flexible peptides, and thus enabled ligand/peptide binding thermodynamics and kinetics calculations. We will also present relevant application studies in simulations of important drug targets and future perspectives for rational computer-aided drug design.

Challenges and frontiers of computational modelling of biomolecular recognition

Biomolecular recognition including binding of small molecules, peptides and proteins to their target receptors plays a key role in cellular function and has been targeted for therapeutic drug design. However, the high flexibility of biomolecules and slow binding and dissociation processes have presented challenges for computational modelling. Here, we review the challenges and computational approaches developed to characterise biomolecular binding, including molecular docking, molecular dynamics simulations (especially enhanced sampling) and machine learning. Further improvements are still needed in order to accurately and efficiently characterise binding structures, mechanisms, thermodynamics and kinetics of biomolecules in the future.

Peptide Dynamics and Metadynamics: Leveraging Enhanced Sampling Molecular Dynamics to Robustly Model Long-Timescale Transitions

Molecular dynamics simulations can in theory reveal the thermodynamics and kinetics of peptide conformational transitions at atomic-level resolution. However, even with modern computing power, they are limited in the timescales they can sample, which is especially problematic for peptides that are fully or partially disordered. Here, we discuss how the enhanced sampling methods accelerated molecular dynamics (aMD) and metadynamics can be leveraged in a complementary fashion to quickly explore conformational space and then robustly quantify the underlying free energy landscape. We apply these methods to two peptides that have an intrinsically disordered nature, the histone H3 and H4 N-terminal tails, and use metadynamics to compute the free energy landscape along collective variables discerned from aMD simulations. Results show that these peptides are largely disordered, with a slight preference for α-helical structures.

Development of enhanced conformational sampling methods to probe the activation landscape of GPCRs

G protein-coupled receptors (GPCRs) make up the largest superfamily of integral membrane proteins and play critical signal transduction roles in many physiological processes. Developments in molecular biology, biophysical, biochemical, pharmacological, and computational techniques aimed at these important therapeutic targets are beginning to provide unprecedented details on the structural as well as functional basis of their pleiotropic signaling mediated by G proteins, β arrestins, and other transducers. This pleiotropy presents a pharmacological challenge as the same ligand-receptor interaction can cause a therapeutic effect as well as an undesirable on-target side-effect through different downstream pathways. GPCRs don't function as simple binary on-off switches but as finely tuned shape-shifting machines described by conformational ensembles, where unique subsets of conformations may be responsible for specific signaling cascades. X-ray crystallography and more recently cryo-electron microscopy are providing snapshots of some of these functionally-important receptor conformations bound to ligands and/or transducers, which are being utilized by computational methods to describe the dynamic conformational energy landscape of GPCRs. In this chapter, we review the progress in computational conformational sampling methods based on molecular dynamics and discrete sampling approaches that have been successful in complementing biophysical and biochemical studies on these receptors in terms of their activation mechanisms, allosteric effects, actions of biased ligands, and effects of pathological mutations. Some of the sampled simulation time scales are beginning to approach receptor activation time scales. The list of conformational sampling methods and example uses discussed is not exhaustive but includes representative examples that have pushed the limits of classical molecular dynamics and discrete sampling methods to describe the activation energy landscape of GPCRs.

Structure and Function of the Refined C-Terminal Loop in Imidazole Glycerol Phosphate Dehydratase from Different Homologs

IGPD is an essential metalloenzyme that catalyzes histidine biosynthesis. We found that its C-terminus loop region has a vital role in determining enzyme activity but has been hardly mentioned before. In this work, we focused on the dynamic feature and function of C-Loop in Arabidopsis thaliana and Saccharomyces cerevisiae IGPD (At_IGPD and Sc_IGPD, respectively). Due to the high flexibility of this region, we performed a total of 3.4 μs of accelerated molecular dynamics simulation to enhance sampling. Inhibitor C348 in At-IGPD exhibited instability in the later stage of simulation, while the characteristic sequence in Sc_IGPD reduced solvent interference and significantly restrained the interaction mode. For the C-Loop-assisted ligand-binding process, we proposed a "Lock-Lid" model. Meanwhile, the dissociated ligand in At_IGPD served as a probe, a metastable pocket was determined at the root of C-Loop, and its rationality was proved by theoretical verification and enzyme mutation experiments. This study complemented the important structural features of C-Loop and provided a basis for the design of selective inhibitors. Considering the absence in mammals, we suggested that IGPD could be a promising germicide target.

Probing Allosteric Regulation Mechanism of W7.35 on Agonist-Induced Activity for μOR by Mutation Simulation

The residue located at 15 positions before the most conserved residue in TM7 (7.35 of Ballesteros-Weinstein number) plays important roles in ligand binding and the receptor activity for class A GPCRs. Nevertheless, its regulation mechanism has not been clearly clarified in experiments, and some controversies also exist for its impact on μ-opioid receptors (μOR) bound by agonists. Thus, we chose the μ-opioid receptor (μOR) of class A GPCRs as a representative and utilized a microsecond accelerated molecular dynamics simulation (aMD) coupled with a protein structure network (PSN) to explore the effect of W318^7.35 on its functional activity induced by the agonist endomorphin2 mainly by a comparison of the wild system and its W7.35A mutant. When endomorphin2 binds to the wild-type μOR, TM6 in μOR moves outward to form an open intracellular conformation that is beneficial to accommodating the β-arrestin transducer, rather than the G-protein transducer due to the clash with the α5 helix of G-protein, thus acting as a β-arrestin biased agonist. However, the W318A mutation induces the intracellular part of μOR to form a closed state, which disfavors coupling with either G-protein or β-arrestin. The allosteric pathway analysis further reveals that the binding of endomorphin2 to the wild-type μOR transmits more activation signals to the β-arrestin binding site while the W318A mutation induces more structural signals to transmit to common binding residues of the G protein and β-arrestin. More interestingly, the residue at the 7.35 position regulates the shortest allosteric pathway in indirect ways by influencing the interactions between other ligand-binding residues and endomorphin2. W293^6.48 and F289^6.44 are important for regulating the different activities of μOR induced either by the agonist or by the mutation. Y336^7.53, F343^8.50, and D340^8.47 play crucial roles in activating the β-arrestin biased signal induced by the agonist endomorphin2, while L158^3.43 and V286^6.41 devote important contributions to the change in the activity of endomorphin2 from the β-arrestin biased agonist to the antagonist upon the W318A mutation.

Computer analysis of the relation between hydrogen bond stability in SOD1 mutants and the survival time of amyotrophic lateral sclerosis patients

BACKGROUND AND OBJECTIVE

Mutations in the SOD1 protein can lead to the death of motor neurons, which, in turn, causes an incurable disease called amyotrophic lateral sclerosis (ALS). At the same time, the mechanism of the onset and development of this disease is not fully understood and is often contradictory.

METHODS

Accelerated Molecular Dynamics as implemented in the OpenMM library, principal component analysis, regression analysis, random forest method.

RESULTS

The stability of hydrogen bonds in 72 mutants of the SOD1 protein was calculated. Principal component analysis was carried out. Based on ten principal components acting as predictors, a multiple linear regression model was constructed. An analysis of the correlation of these ten principal components with the initial values of the stability of hydrogen bonds made it possible to characterize the contribution of known structurally and functionally important sites in the SOD1 to the scatter of ALS patients' survival time.

CONCLUSION

Such an analysis made it possible to put forward hypotheses about the relationship between the stabilizing and destabilizing effects of mutations in different structurally and functionally important regions of SOD1 with the patients's survival time.

Gaussian accelerated molecular dynamics (GaMD): principles and applications

Gaussian accelerated molecular dynamics (GaMD) is a robust computational method for simultaneous unconstrained enhanced sampling and free energy calculations of biomolecules. It works by adding a harmonic boost potential to smooth biomolecular potential energy surface and reduce energy barriers. GaMD greatly accelerates biomolecular simulations by orders of magnitude. Without the need to set predefined reaction coordinates or collective variables, GaMD provides unconstrained enhanced sampling and is advantageous for simulating complex biological processes. The GaMD boost potential exhibits a Gaussian distribution, thereby allowing for energetic reweighting via cumulant expansion to the second order (i.e., "Gaussian approximation"). This leads to accurate reconstruction of free energy landscapes of biomolecules. Hybrid schemes with other enhanced sampling methods, such as the replica exchange GaMD (rex-GaMD) and replica exchange umbrella sampling GaMD (GaREUS), have also been introduced, further improving sampling and free energy calculations. Recently, new "selective GaMD" algorithms including the ligand GaMD (LiGaMD) and peptide GaMD (Pep-GaMD) enabled microsecond simulations to capture repetitive dissociation and binding of small-molecule ligands and highly flexible peptides. The simulations then allowed highly efficient quantitative characterization of the ligand/peptide binding thermodynamics and kinetics. Taken together, GaMD and its innovative variants are applicable to simulate a wide variety of biomolecular dynamics, including protein folding, conformational changes and allostery, ligand binding, peptide binding, protein-protein/nucleic acid/carbohydrate interactions, and carbohydrate/nucleic acid interactions. In this review, we present principles of the GaMD algorithms and recent applications in biomolecular simulations and drug design.

From the Design to the In Vivo Evaluation of Benzohomoadamantane-Derived Soluble Epoxide Hydrolase Inhibitors for the Treatment of Acute Pancreatitis

The pharmacological inhibition of soluble epoxide hydrolase (sEH) is efficient for the treatment of inflammatory and pain-related diseases. Numerous potent sEH inhibitors (sEHIs) present adamantyl or phenyl moieties, such as the clinical candidates AR9281 or EC5026. Herein, in a new series of sEHIs, these hydrophobic moieties have been merged in a benzohomoadamantane scaffold. Most of the new sEHIs have excellent inhibitory activities against sEH. Molecular dynamics simulations suggested that the addition of an aromatic ring into the adamantane scaffold produced conformational rearrangements in the enzyme to stabilize the aromatic ring of the benzohomoadamantane core. A screening cascade permitted us to select a candidate for an in vivo efficacy study in a murine model of cerulein-induced acute pancreatitis. The administration of 22 improved the health status of the animals and reduced pancreatic damage, demonstrating that the benzohomoadamantane unit is a promising scaffold for the design of novel sEHIs.

A novel RNA pol II CTD interaction site on the mRNA capping enzyme is essential for its allosteric activation

Recruitment of the mRNA capping enzyme (CE/RNGTT) to the site of transcription is essential for the formation of the 5' mRNA cap, which in turn ensures efficient transcription, splicing, polyadenylation, nuclear export and translation of mRNA in eukaryotic cells. The CE GTase is recruited and activated by the Serine-5 phosphorylated carboxyl-terminal domain (CTD) of RNA polymerase II. Through the use of molecular dynamics simulations and enhanced sampling techniques, we provide a systematic and detailed characterization of the human CE-CTD interface, describing the effect of the CTD phosphorylation state, length and orientation on this interaction. Our computational analyses identify novel CTD interaction sites on the human CE GTase surface and quantify their relative contributions to CTD binding. We also identify, for the first time, allosteric connections between the CE GTase active site and the CTD binding sites, allowing us to propose a mechanism for allosteric activation. Through binding and activity assays we validate the novel CTD binding sites and show that the CDS2 site is essential for CE GTase activity stimulation. Comparison of the novel sites with cocrystal structures of the CE-CTD complex in different eukaryotic taxa reveals that this interface is considerably more conserved than previous structures have indicated.

Cardiolipin interactions with cytochrome c increase tyrosine nitration yields and site-specificity

The interaction between cytochrome c and cardiolipin is a relevant process in the mitochondrial redox homeostasis, playing roles in the mechanism of electron transfer to cytochrome c oxidase and also modulating cytochrome c conformation, reactivity and function. Peroxynitrite is a widespread nitrating agent formed in mitochondria under oxidative stress conditions, and can result in the formation of tyrosine nitrated cytochrome c. Some of the nitro-cytochrome c species undergo conformational changes at physiological pH and increase its peroxidase activity. In this work we evaluated the influence of cardiolipin on peroxynitrite-mediated cytochrome c nitration yields and site-specificity. Our results show that cardiolipin enhances cytochrome c nitration by peroxynitrite and targets it to heme-adjacent Tyr67. Cytochrome c nitration also modifies the affinity of protein with cardiolipin. Using a combination of experimental techniques and computer modeling, it is concluded that structural modifications in the Tyr67 region are responsible for the observed changes in protein-derived radical and tyrosine nitration levels, distribution of nitrated proteoforms and affinity to cardiolipin. Increased nitration of cytochrome c in presence of cardiolipin within mitochondria and the gain of peroxidatic activity could then impact events such as the onset of apoptosis and other processes related to the disruption of mitochondrial redox homeostasis.

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.

Elucidating Solution Structures of Cyclic Peptides Using Molecular Dynamics Simulations

Protein-protein interactions are vital to biological processes, but the shape and size of their interfaces make them hard to target using small molecules. Cyclic peptides have shown promise as protein-protein interaction modulators, as they can bind protein surfaces with high affinity and specificity. Dozens of cyclic peptides are already FDA approved, and many more are in various stages of development as immunosuppressants, antibiotics, antivirals, or anticancer drugs. However, most cyclic peptide drugs so far have been natural products or derivatives thereof, with de novo design having proven challenging. A key obstacle is structural characterization: cyclic peptides frequently adopt multiple conformations in solution, which are difficult to resolve using techniques like NMR spectroscopy. The lack of solution structural information prevents a thorough understanding of cyclic peptides' sequence-structure-function relationship. Here we review recent development and application of molecular dynamics simulations with enhanced sampling to studying the solution structures of cyclic peptides. We describe novel computational methods capable of sampling cyclic peptides' conformational space and provide examples of computational studies that relate peptides' sequence and structure to biological activity. We demonstrate that molecular dynamics simulations have grown from an explanatory technique to a full-fledged tool for systematic studies at the forefront of cyclic peptide therapeutic design.

Anti-TNF Alpha Antibody Humira with pH-dependent Binding Characteristics: A constant-pH Molecular Dynamics, Gaussian Accelerated Molecular Dynamics, and In Vitro Study

Humira is a monoclonal antibody that binds to TNF alpha, inactivates TNF alpha receptors, and inhibits inflammation. Neonatal Fc receptors can mediate the transcytosis of Humira-TNF alpha complex structures and process them toward degradation pathways, which reduces the therapeutic effect of Humira. Allowing the Humira-TNF alpha complex structures to dissociate to Humira and soluble TNF alpha in the early endosome to enable Humira recycling is crucial. We used the cytoplasmic pH (7.4), the early endosomal pH (6.0), and pKa of histidine side chains (6.0-6.4) to mutate the residues of complementarity-determining regions with histidine. Our engineered Humira (W1-Humira) can bind to TNF alpha in plasma at neutral pH and dissociate from the TNF alpha in the endosome at acidic pH. We used the constant-pH molecular dynamics, Gaussian accelerated molecular dynamics, two-dimensional potential mean force profiles, and in vitro methods to investigate the characteristics of W1-Humira. Our results revealed that the proposed Humira can bind TNF alpha with pH-dependent affinity in vitro. The W1-Humira was weaker than wild-type Humira at neutral pH in vitro, and our prediction results were close to the in vitro results. Furthermore, our approach displayed a high accuracy in antibody pH-dependent binding characteristics prediction, which may facilitate antibody drug design. Advancements in computational methods and computing power may further aid in addressing the challenges in antibody drug design.

Unveiling conformational dynamics changes of H-Ras induced by mutations based on accelerated molecular dynamics

Uncovering molecular basis with regard to the conformational change of two switches I and II in the GppNHp (GNP)-bound H-Ras is highly significant for the understanding of Ras signaling. For this purpose, accelerated molecular dynamics (aMD) simulations and principal component (PC) analysis are integrated to probe the effect of mutations G12V, T35S and Q61K on conformational transformation between two switches of the GNP-bound H-Ras. The RMSF and cross-correlation analyses suggest that three mutations exert a vital effect on the flexibility and internal dynamics of two switches in the GNP-bound H-Ras. The results stemming from PC analysis indicate that two switches in the GNP-bound WT H-Ras tend to form a closed state in most conformations, while those in the GNP-bound mutated H-Ras display transformation between different states. This conclusion is further supported by free energy landscapes constructed by using the distances of residues 12 away from 35 and 35 away from 61 as reaction coordinates and different experimental studies. Interaction scanning is performed on aMD trajectories and the information shows that conformational transformations of two switches I and II induced by mutations extremely affect the GNP-residue interactions. Meanwhile, the scanning results also signify that residues G15, A18, F28, K117, A146 and K147 form stable contacts with GNP, while residues D30, E31, Y32, D33, P34 and E62 in two switches I and II produce unstable contacts with GNP. This study not only reveals dynamic behavior changes of two switches in H-Ras induced by mutations, but also unveils general principles and mechanisms with regard to functional conformational changes of H-Ras.

Molecular Dynamics Simulation of Cellulose Synthase Subunit D Octamer with Cellulose Chains from Acetic Acid Bacteria: Insight into Dynamic Behaviors and Thermodynamics on Substrate Recognition

The present study reports the building of a computerized model and molecular dynamics (MD) simulation of cellulose synthase subunit D octamer (CesD) from Komagataeibacter hansenii. CesD was complexed with four cellulose chains having DP = 12 (G12) by model building, which revealed unexpected S-shaped pathways with bending regions. Combined conventional and accelerated MD simulations of CesD complex models were carried out, while the pyranose ring conformations of the glucose residues were restrained to avoid undesirable deviations of the ring conformation from the ⁴C₁ form. The N-terminal regions and parts of the secondary structures of CesD established appreciable contacts with the G12 chains. Hybrid quantum mechanical (QM) and molecular mechanical (MM) simulations of the CesD complex model were performed. Glucose residues located at the pathway bends exhibited reversible changes to the ring conformation into either skewed or boat forms, which might be related to the function of CesD in regulating microfibril production.

Unravelling the molecular basis of AM-6494 high potency at BACE1 in Alzheimer's disease: an integrated dynamic interaction investigation

β-amyloid precursor protein cleaving enzyme1 (BACE1) has prominently been an important drug design target implicated in Alzheimer's disease pathway. The failure rate of most of the already tested drugs at different clinical phases remains a major concern. Recently, AM-6494 was reported as a novel potent, highly selective, and orally effective inhibitor against BACE1. AM-6494 displayed no alteration of skin/fur colour in animal studies, an adverse effect common to previous BACE1 inhibitors. However, the atomistic molecular mechanism of BACE1 inhibition by AM-6494 remains unclear. To elucidate the binding mechanism of AM-6494 relative to umibecestat (CNP-520) as well as the structural changes when bound to BACE1, advanced computational techniques such as accelerated MD simulation and principal component analysis have been utilised. The results demonstrated higher binding affinity of AM-6494 at BACE1 with van der Waals as dominant energy contributor compared to umibecestat. Conformational monitoring of the β-hairpin flap covering the active site revealed an effective flap closure when bound with AM-6494 compared to CNP-520, which predominantly alternates between semi-open and closed conformations. The observed effective flap closure of AM-6494 explains its higher inhibitory power towards BACE1. Besides the catalytic Asp32/228 dyad, Tyr14, Leu30, Tyr71 and Gly230 represent critical residues in the potency of these inhibitors at BACE1 binding interface. The findings highlighted in this research provide a basis to explain AM-6494 high inhibitory potency and might assist in the design of new inhibitors with improved selectivity and potency for BACE1.

Characterizing an allosteric inhibitor-induced inactive state in with-no-lysine kinase 1 using Gaussian accelerated molecular dynamics simulations

The binding of an allosteric inhibitor in WNK1 leads to the inactive state.

Understanding the Mechanism of Activation/Deactivation of GLP-1R via Accelerated Molecular Dynamics Simulation

Glucagon-like peptide-1 receptor (GLP-1R), as a member of the class B G protein-coupled receptors (GPCRs), plays a crucial role in regulating blood glucose level signal recognition through its activation. The conformation changes during the activation pathway are of particular importance for its function. To investigate the activation mechanism of GLP-1R, the crystal structures of active and inactive forms are chosen to perform a total of 2 μs of accelerated molecular dynamics (aMD) simulations and 400ns of conventional molecular dynamics (cMD) simulations. With the aid of structural analysis and potential of mean force (PMF) calculations, we reveal the role of different helices in the activation and deactivation process and obtain the intermediate states during activation and deactivation that are difficult to capture in experiments. Protein structure network (PSN) was utilised to clarify the allosteric communication pathways of activation and deactivation and reveal the mechanisms of its activation and deactivation. The results could advance our understanding of the activation mechanism of GLP-1R and the related drug design.

Polyreactive Broadly Neutralizing B cells Are Selected to Provide Defense against Pandemic Threat Influenza Viruses

Polyreactivity is the ability of a single antibody to bind to multiple molecularly distinct antigens and is a common feature of antibodies induced upon pathogen exposure. However, little is known about the role of polyreactivity during anti-influenza virus antibody responses. By analyzing more than 500 monoclonal antibodies (mAbs) derived from B cells induced by numerous influenza virus vaccines and infections, we found mAbs targeting conserved neutralizing influenza virus hemagglutinin epitopes were polyreactive. Polyreactive mAbs were preferentially induced by novel viral exposures due to their broad viral binding breadth. Polyreactivity augmented mAb viral binding strength by increasing antibody flexibility, allowing for adaption to imperfectly conserved epitopes. Lastly, we found affinity-matured polyreactive B cells were typically derived from germline polyreactive B cells that were preferentially selected to participate in B cell responses over time. Together, our data reveal that polyreactivity is a beneficial feature of antibodies targeting conserved epitopes.

Unravelling the mechanism of pH-regulation in dinoflagellate luciferase

Dinoflagellates are the dominant source of bioluminescence in coastal waters. The luminescence reaction involves the oxidation of luciferin by a luciferase enzyme, which only takes place at low pH. The pH-dependence has previously been linked to four conserved histidines. It has been suggested that their protonation might induce a conformational change in the enzyme, thereby allowing substrate access to the binding pocket. Yet, the precise mechanism of luciferase activation has remained elusive. Here, we use computational tools to predict the open structure of the luciferase in Lingulodinium polyedra and to decipher the nature of the opening mechanism. Through accelerated molecular dynamics simulations, we demonstrate that the closed-open conformational change likely takes place via a tilt of the pH-regulatory helix-loop-helix domain. Moreover, we propose that the molecular basis for the transition is electrostatic repulsion between histidine-cation pairs, which destabilizes the closed conformation at low pH. Finally, by simulating truncated mutants, we show that eliminating the C-terminus alters the shape of the active site, effectively inactivating the luciferase.

Simulating Multiple Substrate-Binding Events by γ-Glutamyltransferase Using Accelerated Molecular Dynamics

γ-Glutamyltransferase (GGT) is an enzyme that uses γ-glutamyl compounds as substrates and catalyzes their transfer to a water molecule or an acceptor substrate with varied physiological function in bacteria, plants, and animals. Crystal structures of GGT are known for different species and in different states of the chemical reaction; however, the structural dynamics of the substrate binding to the catalytic site of GGT are unknown. Here, we modeled Escherichia coli GGT's glutamine binding by using a swarm of accelerated molecular dynamics (aMD) simulations. Characterization of multiple binding events identified three structural binding motifs composed of polar residues in the binding pocket that govern glutamine binding into the active site. Simulated open and closed conformations of a lid-loop protecting the binding cavity suggest its role as a gating element by allowing or blocking substrates entry into the binding pocket. Partially open states of the lid-loop are accessible within thermal fluctuations, while the estimated free energy cost of a complete open state is 2.4 kcal/mol. Our results suggest that both specific electrostatic interactions and GGT conformational dynamics dictate the molecular recognition of substrate-GGT complexes.

Glycan-mediated functional assembly of IL-1RI: structural insights into completion of the current description for immune response

Interleukin 1 Receptor type I (IL-1RI) is a multi-domain transmembrane receptor that triggers the inflammatory response. Understanding its detailed mechanism of action is crucial for treating immune disorders. IL-1RI is activated upon formation of its functional assembly that occurs by binding of the IL-1 cytokine and the accessory protein (Il-1RAcP) to it. X-ray crystallography, small-Angle X-ray Scattering and molecular dynamics simulation studies showed that IL-1RI adopts two types of 'compact' and 'extended' conformational states in its dynamical pattern. Furthermore, glycosylation has shown to play a critical role in its activation process. Here, classical and accelerated atomistic molecular dynamics were carried out to examine the role of full glycosylation of IL-1RI and IL-1RAcP in arrangement of the functional assembly. Simulations showed that the 'compact' and 'extended' IL-1RI form two types of 'cytokine-inaccessible-non-signaling' and 'cytokine-accessible-signaling' assemblies with the IL-1RacP, respectively that are both abiding in the presence of glycans. Suggesting that the cytokine binding to IL-1RI is not required for the formation of IL-1RI-IL-1RAcP complex and the 'compact' complex could act as a down-regulatory mechanism. The 'extended' complex is maintained by formation of several persistent hydrogen bonds between the IL-1RI-IL-1RAcP inter-connected glycans. Taken together, it was shown that full glycosylation regulates formation of the IL-1RI functional assembly and play critical role in cytokine biding and triggering the IL-1RI involved downstream pathways in the cell.Communicated by Ramaswamy H. Sarma.

Nucleotide Loading Modes of Human RNA Polymerase II as Deciphered by Molecular Simulations

Mapping the route of nucleoside triphosphate (NTP) entry into the sequestered active site of RNA polymerase (RNAP) has major implications for elucidating the complete nucleotide addition cycle. Constituting a dichotomy that remains to be resolved, two alternatives, direct NTP delivery via the secondary channel (CH2) or selection to downstream sites in the main channel (CH1) prior to catalysis, have been proposed. In this study, accelerated molecular dynamics simulations of freely diffusing NTPs about RNAPII were applied to refine the CH2 model and uncover atomic details on the CH1 model that previously lacked a persuasive structural framework to illustrate its mechanism of action. Diffusion and binding of NTPs to downstream DNA, and the transfer of a preselected NTP to the active site, are simulated for the first time. All-atom simulations further support that CH1 loading is transcription factor IIF (TFIIF) dependent and impacts catalytic isomerization. Altogether, the alternative nucleotide loading systems may allow distinct transcriptional landscapes to be expressed.

Zinc-mediated conformational preselection mechanism in the allosteric control of DNA binding to the zinc transcriptional regulator (ZitR)

The zinc transcriptional regulator (ZitR) functions as a metalloregulator that fine tunes transcriptional regulation through zinc-dependent DNA binding. However, the molecular mechanism of zinc-driven allosteric control of the DNA binding to ZitR remains elusive. Here, we performed enhanced sampling accelerated molecular dynamics simulations to figure out the mechanism, revealing the role of protein dynamics in the zinc-induced allosteric control of DNA binding to ZitR. The results suggest that zinc-free ZitR samples distinct conformational states, only a handful of which are compatible with DNA binding. Remarkably, zinc binding reduces the conformational plasticity of the DNA-binding domain of ZitR, promoting the population shift in the ZitR conformational ensemble towards the DNA binding-competent conformation. Further co-binding of DNA to the zinc–ZitR complex stabilizes this competent conformation. These findings suggest that ZitR–DNA interactions are allosterically regulated in a zinc-mediated conformational preselection manner, highlighting the importance of conformational dynamics in the regulation of transcription factor family.