Gaussian Accelerated Molecular Dynamics Simulations Research Articles

Reinforcing Tunnel Network Exploration in Proteins Using Gaussian Accelerated Molecular Dynamics.

Tunnels are structural conduits in biomolecules responsible for transporting chemical compounds and solvent molecules from the active site. They have been shown to be present in a wide variety of enzymes across all functional and structural classes. However, the study of such pathways is experimentally challenging, because they are typically transient. Computational methods, such as molecular dynamics (MD) simulations, have been successfully proposed to explore tunnels. Conventional MD (cMD) provides structural details to characterize tunnels but suffers from sampling limitations to capture rare tunnel openings on longer time scales. Therefore, in this study, we explored the potential of Gaussian accelerated MD (GaMD) simulations to improve the exploration of complex tunnel networks in enzymes. We used the haloalkane dehalogenase LinB and its two variants with engineered transport pathways, which are not only well-known for their application potential but have also been extensively studied experimentally and computationally regarding their tunnel networks and their importance in multistep catalytic reactions. Our study demonstrates that GaMD efficiently improves tunnel sampling and allows the identification of all known tunnels for LinB and its two mutants. Furthermore, the improved sampling provided insight into a previously unknown transient side tunnel (ST). The extensive conformational landscape explored by GaMD simulations allowed us to investigate in detail the mechanism of ST opening. We determined variant-specific dynamic properties of ST opening, which were previously inaccessible due to limited sampling of cMD. Our comprehensive analysis supports multiple indicators of the functional relevance of the ST, emphasizing its potential significance beyond structural considerations. In conclusion, our research proves that the GaMD method can overcome the sampling limitations of cMD for the effective study of tunnels in enzymes, providing further means for identifying rare tunnels in enzymes with the potential for drug development, precision medicine, and rational protein engineering.

Multiple Parameter Replica Exchange Gaussian Accelerated Molecular Dynamics for Enhanced Sampling and Free Energy Calculation of Biomolecular Systems.

This study introduces a novel method named multiple parameter replica exchange Gaussian accelerated molecular dynamics (MP-Rex-GaMD), building on the Gaussian accelerated molecular dynamics (GaMD) algorithm. GaMD enhances sampling and retrieves free energy information for biomolecular systems by adding a harmonic boost potential to smooth the potential energy surface without the need for predefined reaction coordinates. Our innovative approach advances the acceleration power and energetic reweighting accuracy of GaMD by incorporating a replica exchange algorithm that enables the exchange of multiple parameters, including the GaMD boost parameters of force constant and energy threshold, as well as temperature. Applying MP-Rex-GaMD to the three model systems of dialanine, chignolin, and HIV protease, we demonstrate its superior capability over conventional molecular dynamics and GaMD simulations in exploring protein conformations and effectively navigating various biomolecular states across energy barriers. MP-Rex-GaMD allows users to accurately map free energy landscapes through energetic reweighting, capturing the ensemble of biomolecular states from low-energy conformations to rare high-energy transitions within practical computational time scales.

Insights into the Interaction Mechanisms of Peptide and Non-Peptide Inhibitors with MDM2 Using Gaussian-Accelerated Molecular Dynamics Simulations and Deep Learning.

Inhibiting MDM2-p53 interaction is considered an efficient mode of cancer treatment. In our current study, Gaussian-accelerated molecular dynamics (GaMD), deep learning (DL), and binding free energy calculations were combined together to probe the binding mechanism of non-peptide inhibitors K23 and 0Y7 and peptide ones PDI6W and PDI to MDM2. The GaMD trajectory-based DL approach successfully identified significant functional domains, predominantly located at the helixes α2 and α2', as well as the β-strands and loops between α2 and α2'. The post-processing analysis of the GaMD simulations indicated that inhibitor binding highly influences the structural flexibility and collective motions of MDM2. Calculations of molecular mechanics-generalized Born surface area (MM-GBSA) and solvated interaction energy (SIE) not only suggest that the ranking of the calculated binding free energies is in agreement with that of the experimental results, but also verify that van der Walls interactions are the primary forces responsible for inhibitor-MDM2 binding. Our findings also indicate that peptide inhibitors yield more interaction contacts with MDM2 compared to non-peptide inhibitors. Principal component analysis (PCA) and free energy landscape (FEL) analysis indicated that the piperidinone inhibitor 0Y7 shows the most pronounced impact on the free energy profiles of MDM2, with the piperidinone inhibitor demonstrating higher fluctuation amplitudes along primary eigenvectors. The hot spots of MDM2 revealed by residue-based free energy estimation provide target sites for drug design toward MDM2. This study is expected to provide useful theoretical aid for the development of selective inhibitors of MDM2 family members.

Enhancement of octreotide antiproliferative activity by PEGylated PAMAM dendrimers delivery

AbstractPEGylated PAMAM dendrimers (PEG‐PAMAM) are well‐characterized biomaterials with still unexplored applications as carriers of drugs acting via membrane receptors, such as octreotide. This work confirmed the safety and negligible internalization capacity of fourth‐generation 50%‐PEG‐PAMAM in HEK‐293 cells, to then assessed their supramolecular binding to octreotide through tryptophan quenching experiments and Gaussian‐accelerated molecular dynamics (GaMD) simulations. Tryptophan quenching showed that PEG‐PAMAM binds octreotide with a Kbind of 6 × 106 M−1 and a complex stoichiometry of 1:1.4, unlike native PAMAM. GaMD simulations revealed that octreotide binds at the outer PEG shell of PEG‐PAMAM, potentially hindering the drug from proteolytic degradation and enabling its release at a membrane level. Viability experiments on HeLa, PC‐12, and HEK‐293 cells incubated with increasing concentrations of octreotide in free drug solutions and equimolar mixtures with PEG‐PAMAM confirmed that the PEGylated dendrimer acts as an efficient supramolecular carrier for octreotide and enhances the antiproliferative effects of the drug. Our findings highlight a novel facet for PEG‐PAMAM dendrimers as macromolecular vehicles for peptide or non‐peptide drugs acting via membrane receptor sites.

Mechanism of antagonist ligand binding to REV-ERBα.

REV-ERBα, a therapeutically promising nuclear hormone receptor, plays a crucial role in regulating various physiological processes such as the circadian clock, inflammation, and metabolism. However, the availability of chemical probes to investigate the pharmacology of this receptor is limited, with SR8278 being the only identified synthetic antagonist. Moreover, no X-ray crystal structures are currently available that demonstrate the binding of REV-ERBα to antagonist ligands. This lack of structural information impedes the development of targeted therapeutics. To address this issue, we employed Gaussian accelerated molecular dynamics (GaMD) simulations to investigate the binding pathway of SR8278 to REV-ERBα. For comparison, we also used GaMD to observe the ligand binding process of STL1267, for which an X-ray structure is available. GaMD simulations successfully captured the binding of both ligands to the receptor's orthosteric site and predicted the ligand binding pathway and important amino acid residues involved in the antagonist SR8278 binding. This study highlights the effectiveness of GaMD in investigating protein-ligand interactions, particularly in the context of drug recognition for nuclear hormone receptors.

RedOx regulation of LRRK2 kinase activity by active site cysteines

Mutations of the human leucine-rich repeat kinase 2 (LRRK2) have been associated with both, idiopathic and familial Parkinson’s disease (PD). Most of these pathogenic mutations are located in the kinase domain (KD) or GTPase domain of LRRK2. In this study we describe a mechanism in which protein kinase activity can be modulated by reversible oxidation or reduction, involving a unique pair of adjacent cysteines, the “CC” motif. Among all human protein kinases, only LRRK2 contains this “CC” motif (C2024 and C2025) in the Activation Segment (AS) of the kinase domain. In an approach combining site-directed mutagenesis, biochemical analyses, cell-based assays, and Gaussian accelerated Molecular Dynamics (GaMD) simulations we could attribute a role for each of those cysteines. We employed reducing and oxidizing agents with potential clinical relevance to investigate effects on kinase activity and microtubule docking. We find that each cysteine gives a distinct contribution: the first cysteine, C2024, is essential for LRRK2 protein kinase activity, while the adjacent cysteine, C2025, contributes significantly to redox sensitivity. Implementing thiolates (R-S-) in GaMD simulations allowed us to analyse how each of the cysteines in the “CC” motif interacts with its surrounding residues depending on its oxidation state. From our studies we conclude that oxidizing agents can downregulate kinase activity of hyperactive LRRK2 PD mutations and may provide promising tools for therapeutic strategies.

Mechanistic Insights into Peptide Binding and Deactivation of an Adhesion G Protein-Coupled Receptor.

Adhesion G protein-coupled receptors (ADGRGs) play critical roles in the reproductive, neurological, cardiovascular, and endocrine systems. In particular, ADGRG2 plays a significant role in Ewing sarcoma cell proliferation, parathyroid cell function, and male fertility. In 2022, a cryo-EM structure was reported for the active ADGRG2 bound by an optimized peptide agonist IP15 and the Gs protein. The IP15 peptide agonist was also modified to antagonists 4PH-E and 4PH-D with mutations of the 4PH residue to Glu and Asp, respectively. However, experimental structures of inactive antagonist-bound ADGRs remain to be resolved, and the activation mechanism of ADGRs such as ADGRG2 is poorly understood. Here, we applied Gaussian accelerated molecular dynamics (GaMD) simulations to probe conformational dynamics of the agonist- and antagonist-bound ADGRG2. By performing GaMD simulations, we were able to identify important low-energy conformations of ADGRG2 in the active, intermediate, and inactive states, as well as explore the binding conformations of each peptide. Moreover, our simulations revealed critical peptide-receptor residue interactions during the deactivation of ADGRG2. In conclusion, through GaMD simulations, we uncovered mechanistic insights into peptide (agonist and antagonist) binding and deactivation of the ADGRG2. These findings will potentially facilitate rational design of new peptide modulators of ADGRG2 and other ADGRs.

Molecular Dynamics Activation of γ-Secretase for Cleavage of the Notch1 Substrate.

γ-Secretase is an intramembrane aspartyl protease complex that cleaves the transmembrane domain of over 150 peptide substrates, including amyloid precursor protein (APP) and the Notch family of receptors, via two conserved aspartates D257 and D385 in the presenilin-1 (PS1) catalytic subunit. However, while the activation of γ-secretase for cleavage of APP has been widely studied, the cleavage of Notch by γ-secretase remains poorly explored. Here, we combined Gaussian accelerated molecular dynamics (GaMD) simulations and mass spectrometry (MS) analysis of proteolytic products to present the first dynamic models for cleavage of Notch by γ-secretase. MS showed that γ-secretase cleaved the WT Notch at Notch residue G34, while cleavage of the L36F mutant Notch occurred at Notch residue C33. Initially, we prepared our simulation systems starting from the cryoEM structure of Notch-bound γ-secretase (PDB: 6IDF) and failed to capture the proper cleavages of WT and L36F Notch by γ-secretase. We then discovered an incorrect registry of the Notch substrate in the PS1 active site through alignment of the experimental structure of Notch-bound (PDB: 6IDF) and APP-bound γ-secretase (PDB: 6IYC). Every residue of the APP substrate was systematically mutated to the corresponding Notch residue to prepare a resolved model of Notch-bound γ-secretase complexes. GaMD simulations of the resolved model successfully captured γ-secretase activation for proper cleavages of both WT and L36F mutant Notch. Our findings presented here provided mechanistic insights into the structural dynamics and enzyme-substrate interactions required for γ-secretase activation for cleavage of Notch and other substrates.

Deep Learning Dynamic Allostery of G-Protein-Coupled Receptors.

G-protein-coupled receptors (GPCRs) make up the largest superfamily of human membrane proteins and represent primary targets of ∼1/3 of currently marketed drugs. Allosteric modulators have emerged as more selective drug candidates compared with orthosteric agonists and antagonists. However, many X-ray and cryo-EM structures of GPCRs resolved so far exhibit negligible differences upon the binding of positive and negative allosteric modulators (PAMs and NAMs). The mechanism of dynamic allosteric modulation in GPCRs remains unclear. In this work, we have systematically mapped dynamic changes in free energy landscapes of GPCRs upon binding of allosteric modulators using the Gaussian accelerated molecular dynamics (GaMD), deep learning (DL), and free energy prOfiling Workflow (GLOW). GaMD simulations were performed for a total of 66 μs on 44 GPCR systems in the presence and absence of the modulator. DL and free energy calculations revealed significantly reduced dynamic fluctuations and conformational space of GPCRs upon modulator binding. While the modulator-free GPCRs often sampled multiple low-energy conformational states, the NAMs and PAMs confined the inactive and active agonist-G-protein-bound GPCRs, respectively, to mostly only one specific conformation for signaling. Such cooperative effects were significantly reduced for binding of the selective modulators to "non-cognate" receptor subtypes. Therefore, GPCR allostery exhibits a dynamic "conformational selection" mechanism. In the absence of available modulator-bound structures as for most current GPCRs, it is critical to use a structural ensemble of representative GPCR conformations rather than a single structure for compound docking ("ensemble docking"), which will potentially improve structure-based design of novel allosteric drugs of GPCRs.

Dynamic Insights into the Self-Activation Pathway and Allosteric Regulation of the Orphan G-Protein-Coupled Receptor GPR52.

Within over 800 members of G-protein-coupled receptors, there are numerous orphan receptors whose endogenous ligands are largely unknown, providing many opportunities for novel drug discovery. However, the lack of an in-depth understanding of the intrinsic working mechanism for orphan receptors severely limits the related rational drug design. The G-protein-coupled receptor 52 (GPR52) is a unique orphan receptor that constitutively increases cellular 5'-cyclic adenosine monophosphate (cAMP) levels without binding any exogenous agonists and has been identified as a promising therapeutic target for central nervous system disorders. Although recent structural biology studies have provided snapshots of both active and inactive states of GPR52, the mechanism of the conformational transition between these states remains unclear. Here, an acceptable self-activation pathway for GPR52 was proposed through 6 μs Gaussian accelerated molecular dynamics (GaMD) simulations, in which the receptor spontaneously transitions from the active state to that matching the inactive crystal structure. According to the three intermediate states of the receptor obtained by constructing a reweighted potential of mean force, how the allosteric regulation occurs between the extracellular orthosteric binding pocket and the intracellular G-protein-binding site is revealed. Combined with the independent gradient model, several important microswitch residues and the allosteric communication pathway that directly links the two regions are both identified. Transfer entropy calculations not only reveal the complex allosteric signaling within GPR52 but also confirm the unique role of ECL2 in allosteric regulation, which is mutually validated with the results of GaMD simulations. Overall, this work elucidates the allosteric mechanism of GPR52 at the atomic level, providing the most detailed information to date on the self-activation of the orphan receptor.

Determining the confromational ensemble of the HIV-1 LTR G-quadruplexes through gaussian-accelerated molecular dynamics using the drude polarizable force field.

Human immunodeficiency virus (HIV) impacts nearly 37.6 million people globally, but there is no effective cure for the infections it causes. HIV-1 is a retrovirus containing a single-stranded RNA genome. After reverse transcription, the 5’ long terminal repeat (LTR) acts as a promoter for viral replication. Two DNA G-quadruplexes (GQs), known as LTR-III and LTR-IV, form within this promoter and inversely regulate viral gene expression. The LTR-III GQ downregulates viral expression and is a quadruplex: duplex hybrid whereas LTR-IV upregulates viral expression and is a parallel GQ containing a single-nucleotide bulge. Their distinct topologies and functional roles suggest their potential to act as selective drug targets for HIV-1.To gain a greater understanding of structure and dynamics of the LTR-III and LTR-IV GQs, we performed conventional molecular dynamics simulations using the Drude polarizable force field. The loop nucleotides in both structures were highly flexible, sampling a variety of conformational states. The LTR-IV loop also formed base pair interactions that limited ion access to its loop cavity and further highlighted two distinct ion binding sites near the backbone tetrad guanines. Within the LTR-III duplex loop, an additional Watson-Crick base pair formed between Ade4:Thy14 and persisted for 40% of the snapshots collected in the total 4-μs simulation time. Analysis of the electric field exerted on Thy14 indicates a preference for base pairing with Ade4 compared to being unpaired as in the NMR ensemble. Gaussian-accelerated molecular dynamics simulations were also performed to identify high and low energy conformational states for subsequent drug targeting. Our results emphasize the importance of electronic polarization in GQ dynamics and can guide future development of antiviral therapeutics.

Activation mechanism of the M5 muscarinic acetylcholine receptor.

The muscarinic acetylcholine receptor family are class A G protein-coupled receptors (GPCRs) that help facilitate the actions of the neurotransmitter acetylcholine throughout the body. Because the M5 subtype (M5R) is exclusively expressed on dopaminergic neurons in the mesolimbic pathway, it is emerging as an attractive therapeutic target for treating addictive disorders. However, the lack of crystal structures on the intermediate and active conformations of the receptor has hampered the design of potent antagonist and agonists. Therefore, this study will explore the active, intermediate, and inactive conformations of an apo- M5R by running 300 ns Gaussian accelerated molecular dynamics (GaMD) simulations on the modelled active state of the receptor (PDB ID: 6OIJ). The active apo-M5R is expected to transition into the intermediate and inactive states because (1) muscarinic receptors are constitutively active but prefer the inactive state in the absence of agonists, and (2) GaMD simulations lower the energy barriers between protein conformations. Principal component analysis will be performed on the trajectories to identify the major movements of the protein during deactivation/activation, while the subregions involved in the transitions will be determined using community network analysis. The expected movements of the M5R include the outward displacement of TM6 and extension of the TM3 into the cytoplasm. Mutagenesis studies on the M5R also suggest that IL2 and IL3 are involved in G-protein coupling, so these loops are speculated to adopt distinct conformations in each conformation. The obtained intermediate and active conformations and the insights on the activation mechanism will aid further drug design initiatives to relieve addictive disorders.

The full activation mechanism of the adenosine A1 receptor revealed by GaMD and Su-GaMD simulations

The full activation process of G protein-coupled receptor (GPCR) plays an important role in cellular signal transduction. However, it remains challenging to simulate the whole process in which the GPCR is recognized and activated by a ligand and then couples to the G protein on a reasonable simulation timescale. Here, we developed a molecular dynamics (MD) approach named supervised (Su) Gaussian accelerated MD (GaMD) by incorporating a tabu-like supervision algorithm into a standard GaMD simulation. By using this Su-GaMD method, from the active and inactive structure of adenosine A1 receptor (A1R), we successfully revealed the full activation mechanism of A1R, including adenosine (Ado)-A1R recognition, preactivation of A1R, and A1R-G protein recognition, in hundreds of nanoseconds of simulations. The binding of Ado to the extracellular side of A1R initiates conformational changes and the preactivation of A1R. In turn, the binding of Gi2 to the intracellular side of A1R causes a decrease in the volume of the extracellular orthosteric site and stabilizes the binding of Ado to A1R. Su-GaMD could be a useful tool to reconstruct or even predict ligand-protein and protein-protein recognition pathways on a short timescale. The intermediate states revealed in this study could provide more detailed complementary structural characterizations to facilitate the drug design of A1R in the future.

Rational Discovery of Microtubule-Stabilizing Peptides.

Microtubule (MT) stabilization is an attractive pharmacological strategy to hamper the progress of neurodegenerative diseases. In this regard, seeking peptides with MT-stabilizing properties has awoken great interest. This work reports the rational discovery of two structurally related MT-stabilizing octapeptides using a combination of protein-peptide docking, conventional molecular dynamics, Gaussian accelerated molecular dynamics (GaMD), and tubulin polymerization assays. FASTA sequences for ∼1000 peptides were crafted from single and double mutants of davunetide (NAP) and docked against the Taxol (TX) site on an octameric MT model representing a portion of the MT wall. Docked peptides were rescored after MM minimization and binding free energy refinement through single-point MM/GBSA calculations. The 60 best-ranked peptides were subjected to 50 ns MD simulations on peptide-MT complexes at the terminal TX site in the octameric Tau-MT model resulting in 11 complexes with occupancies greater than 99% and peptide-protein binding free energies less than -40 kcal/mol. Selected peptides were then examined through 300 ns GaMD simulations in complexes containing two identical ligands at the terminal and intermediate TX sites in the Tau-MT model to account for the differential association of MT-binding peptides to different regions of the MT structure. Six candidates showed a favorable MT-binding potential based on the analysis of interaction frequencies and relative mobilities of the complex components, suggesting a pivotal role of Arg278, Gln281, and Arg369 residues for peptides recognition. Four candidates were predicted to preserve an adequate balance of longitudinal and lateral interactions between tubulin dimers in peptide-MT complexes such that MT-stabilizing effects could be expected. MT polymerization experiments confirmed that four peptides (HAPVSIHQ, NYPVSIHQ, NWPVSIWQ, HAPVSIIQ) exhibit MT-stabilizing activity in vitro with NWPVSIWQ (P43) and HAPVSIIQ (P52) being the most active. Tryptophan quenching assays verified that P43 and P52 bind to nonpolymeric tubulin, whereas viability experiments on HEK cells confirmed their safety to pursue future pharmacological studies. The results herein presented are valuable to making progress in the rational design of MT-stabilizing peptides.

Deciphering Conformational Changes of the GDP-Bound NRAS Induced by Mutations G13D, Q61R, and C118S through Gaussian Accelerated Molecular Dynamic Simulations.

The conformational changes in switch domains significantly affect the activity of NRAS. Gaussian-accelerated molecular dynamics (GaMD) simulations of three separate replicas were performed to decipher the effects of G13D, Q16R, and C118S on the conformational transformation of the GDP-bound NRAS. The analyses of root-mean-square fluctuations and dynamics cross-correlation maps indicated that the structural flexibility and motion modes of the switch domains involved in the binding of NRAS to effectors are highly altered by the G13D, Q61R, and C118Smutations. The free energy landscapes (FELs) suggested that mutations induce more energetic states in NRAS than the GDP-bound WT NRAS and lead to high disorder in the switch domains. The FELs also indicated that the different numbers of sodium ions entering the GDP binding regions compensate for the changes in electrostatic environments caused by mutations, especially for G13D. The GDP–residue interactions revealed that the disorder in the switch domains was attributable to the unstable hydrogen bonds between GDP and two residues, V29 and D30. This work is expected to provide information on the energetic basis and dynamics of conformational changes in switch domains that can aid in deeply understanding the target roles of NRAS in anticancer treatment.

Gaussian Accelerated Molecular Dynamics in OpenMM.

Gaussian accelerated molecular dynamics (GaMD) is a computational technique that provides both unconstrained enhanced sampling and free energy calculations of biomolecules. Here, we present the implementation of GaMD in the OpenMM simulation package and validate it on model systems of alanine dipeptide and RNA folding. For alanine dipeptide, 30 ns GaMD production simulations reproduced free energy profiles of 1000 ns conventional molecular dynamics (cMD) simulations. In addition, GaMD simulations captured the folding pathways of three hyperstable RNA tetraloops (UUCG, GCAA, and CUUG) and binding of the rbt203 ligand to the HIV-1 Tar RNA, both of which involved critical electrostatic interactions such as hydrogen bonding and base stacking. Together with previous implementations, GaMD in OpenMM will allow for wider applications in simulations of proteins, RNA, and other biomolecules.

Novel Dimeric hHv1 Model and Structural Bioinformatic Analysis Reveal an ATP-Binding Site Resulting in a Channel Activating Effect.

The human voltage-gated proton channel (hHv1) is a highly selective ion channel codified by the HVCN1 gene. It plays a fundamental role in several physiological processes such as innate and adaptive immunity, insulin secretion, and sperm capacitation. Moreover, in humans, a higher hHv1 expression/function has been reported in several types of cancer cells. Here we report a multitemplate homology model of the hHv1 channel, built and refined as a dimer in Rosetta. The model was then subjected to extensive Gaussian accelerated molecular dynamics (GaMD) for enhanced conformational sampling, and representative snapshots were extracted by clustering analysis. Combining different structure- and sequence-based methodologies, we predicted a putative ATP-binding site located on the intracellular portion of the channel. Furthermore, GaMD simulations of the ATP-bound dimeric hHv1 model showed that ATP interacts with a cluster of positively charged residues from the cytoplasmic N and C terminal segments. According to the in silico predictions, we found that 3 mM intracellular ATP significantly increases the H+ current mediated by the hHv1 channel expressed in HEK293 cells and measured by the patch-clamp technique in an inside-out configuration (2.86 ± 0.63 fold over control at +40 mV). When ATP was added on the extracellular side, it was not able to activate the channel supporting the idea that the ATP-binding site resides in the intracellular face of the hHV1 channel. In a physiological and pathophysiological context, this ATP-mediated modulation could integrate the cell metabolic state with the H+ efflux, especially in cells where hHv1 channels are relevant for pH regulation, such as pancreatic β-cells, immune cells, and cancer cells.

Mechanism of tethered agonist-mediated signaling by polycystin-1

Polycystin-1 (PC1) is an important unusual G protein-coupled receptor (GPCR) with 11 transmembrane domains, and its mutations account for 85% of cases of autosomal dominant polycystic kidney disease (ADPKD). PC1 shares multiple characteristics with Adhesion GPCRs. These include a GPCR proteolysis site that autocatalytically divides these proteins into extracellular, N-terminal, and membrane-embedded, C-terminal fragments (CTF), and a tethered agonist (TA) within the N-terminal stalk of the CTF that is suggested to activate signaling. However, the mechanism by which a TA can activate PC1 is not known. Here, we have combined functional cellular signaling experiments of PC1 CTF expression constructs encoding wild type, stalkless, and three different ADPKD stalk variants with all-atom Gaussian accelerated molecular dynamics (GaMD) simulations to investigate TA-mediated signaling activation. Correlations of residue motions and free-energy profiles calculated from the GaMD simulations correlated with the differential signaling abilities of wild type and stalk variants of PC1 CTF. They suggested an allosteric mechanism involving residue interactions connecting the stalk, Tetragonal Opening for Polycystins (TOP) domain, and putative pore loop in TA-mediated activation of PC1 CTF. Key interacting residues such as N3074–S3585 and R3848–E4078 predicted from the GaMD simulations were validated by mutagenesis experiments. Together, these complementary analyses have provided insights into a TA-mediated activation mechanism of PC1 CTF signaling, which will be important for future rational drug design targeting PC1.

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.

Mechanism of RNA recognition by a Musashi RNA-binding protein.

The Musashi RNA-binding proteins (RBPs) regulate translation of target mRNAs and maintenance of cell stemness and tumorigenesis. Musashi-1 (MSI1), long considered as an intestinal and neural stem cell marker, has been more recently found to be over expressed in many cancers. It has served as an important drug target for treating acute myeloid leukemia and solid tumors such as ovarian, colorectal and bladder cancer. One of the reported binding targets of MSI1 is Numb, a negative regulator of the Notch signaling. However, the dynamic mechanism of Numb RNA binding to MSI1 remains unknown, largely hindering effective drug design targeting this critical interaction. Here, we have performed extensive all-atom microsecond-timescale simulations using a robust Gaussian accelerated molecular dynamics (GaMD) method, which successfully captured multiple times of spontaneous and highly accurate binding of the Numb RNA from bulk solvent to the MSI1 protein target site. GaMD simulations revealed that Numb RNA binding to MSI1 involved largely induced fit in both the RNA and protein. The simulations also identified important low-energy intermediate conformational states during RNA binding, in which Numb interacted mainly with the β2-β3 loop and C terminus of MSI1. The mechanistic understanding of RNA binding obtained from our GaMD simulations is expected to facilitate rational structure-based drug design targeting MSI1 and other RBPs.