Gaussian Accelerated Molecular Dynamics Research Articles

Mechanistic Studies of Small Molecule Ligands Selective to RNA Single G Bulges.

Small-molecule RNA binders have emerged as an important pharmacological modality. A profound understanding of the ligand selectivity, binding mode, and influential factors governing ligand engagement with RNA targets is the foundation for rational ligand design. Here, we report a novel class of coumarin derivatives exhibiting selective binding affinity towards single G RNA bulges. Harnessing the computational power of all-atom Gaussian accelerated Molecular Dynamics (GaMD) simulations, we unveiled a rare minor groove binding mode of the ligand with a key interaction between the coumarin moiety and the G bulge. This predicted binding mode is consistent with results obtained from structure-activity-relationship (SAR) studies and transverse relaxation measurements by NMR spectroscopy. We further generated 444 molecular descriptors from 69 coumarin derivatives and identified key contributors to the binding events, such as charge state and planarity, by lasso (least absolute shrinkage and selection operator) regression. Strikingly, small structure perturbations on these key contributors, such as the addition of a methyl group that disrupts the planarity of the ligand resulted in > 100-fold reduction in the binding affinity. Our work deepened the understanding of RNA-small molecule interactions and integrated a new generalizable platform for the rational design of selective small-molecule RNA binders.

Overcoming Sampling Issues and Improving Computational Efficiency in Collective-Variable-Based Enhanced-Sampling Simulations: A Tutorial.

This tutorial is designed to help users overcome sampling challenges and improve computational efficiency in collective-variable (CV)-based enhanced-sampling, or importance-sampling, simulations. Toward this end, we introduce well-tempered metadynamics-extended adaptive biasing force (WTM-eABF) and its integration with Gaussian accelerated molecular dynamics (GaMD). Additionally, use will be made of a method for identifying the least-free-energy pathway (LFEP) and multiple concurrent pathways on high-dimensional free-energy surfaces. We illustrate these sampling techniques with the conformational equilibria of trialanine and chignolin in aqueous solution as test cases. This tutorial assumes that the user has prior experience with molecular dynamics (MD) simulations, in general, with the popular program NAMD, and to some extent with Colvars, the module for CV-based calculations. This tutorial can, however, in large measure be used in conjunction with alternate MD engines that support the Colvars module such as GROMACS, LAMMPS, and Tinker-HP.

Specific Substrate Activity of Lotus Root Polyphenol Oxidase: Insights from Gaussian-Accelerated Molecular Dynamics and Markov State Models.

Polyphenol oxidase (PPO) plays a key role in the enzymatic browning process, and this study employed Gaussian-accelerated molecular dynamics (GaMD) simulations to investigate the catalytic efficiency mechanisms of lotus root PPO with different substrates, including catechin, epicatechin, and chlorogenic acid, as well as the inhibitor oxalic acid. Key findings reveal significant conformational changes in PPO that correlate with its enzymatic activity. Upon substrate binding, the alpha-helix in the Q53-D63 region near the copper ion extends, likely stabilizing the active site and enhancing catalysis. In contrast, this helix is disrupted in the presence of the inhibitor, resulting in a decrease in enzymatic efficiency. Additionally, the F350-V378 region, which covers the substrate-binding site, forms an alpha-helix upon substrate binding, further stabilizing the substrate and promoting catalytic function. However, this alpha-helix does not form when the inhibitor is bound, destabilizing the binding site and contributing to inhibition. These findings offer new insights into the substrate-specific and inhibitor-induced structural dynamics of lotus root PPO, providing valuable information for enhancing food processing and preservation techniques.

Structural Models of Human Norepinephrine Transporter Ensemble Reveal the Allosteric Sites and Ligand-Binding Mechanism.

The norepinephrine transporter (NET) plays a pivotal role in recycling norepinephrine (NE) from the synaptic cleft. However, the structures referring to the conformational heterogeneity of NET during the transport cycle remain poorly understood. Here, three structural models of NE bound to the orthosteric site of NET in outward-open (OOholo), outward-occluded (OCholo), and inward-open (IOholo) conformations were first obtained using the multistate structures of serotonin transporter as templates and further characterized through Gaussian-accelerated molecular dynamics and free energy reweighting. Analysis of the structures revealed eight potential allosteric sites on the functional-specific states of NET. One of the pharmacologically relevant pockets located at the extracellular vestibule was further verified by simulating the binding behaviors of a clinical trial drug χ-MrIA that is allosterically regulating NET. These structural and energetic insights into NET advanced our understanding of NE reuptake and paved the way for discovering novel molecules targeting the allosteric sites.

Conformations of KRAS4B Affected by Its Partner Binding and G12C Mutation: Insights from GaMD Trajectory-Image Transformation-Based Deep Learning.

Binding of partners and mutations highly affects the conformational dynamics of KRAS4B, which is of significance for deeply understanding its function. Gaussian accelerated molecular dynamics (GaMD) simulations followed by deep learning (DL) and principal component analysis (PCA) were carried out to probe the effect of G12C and binding of three partners NF1, RAF1, and SOS1 on the conformation alterations of KRAS4B. DL reveals that G12C and binding of partners result in alterations in the contacts of key structure domains, such as the switch domains SW1 and SW2 together with the loops L4, L5, and P-loop. Binding of NF1, RAF1, and SOS1 constrains the structural fluctuation of SW1, SW2, L4, and L5; on the contrary, G12C leads to the instability of these four structure domains. The analyses of free energy landscapes (FELs) and PCA also show that binding of partners maintains the stability of the conformational states of KRAS4B while G12C induces greater mobility of the switch domains SW1 and SW2, which produces significant impacts on the interactions of GTP with SW1, L4, and L5. Our findings suggest that partner binding and G12C play important roles in the activity and allosteric regulation of KRAS4B, which may theoretically aid in further understanding the function of KRAS4B.

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.

Interactions between Inhibitors and 5-Lipoxygenase: Insights from Gaussian Accelerated Molecular Dynamics and Markov State Models.

Inflammation is a protective stress response triggered by external stimuli, with 5-lipoxygenase (5LOX) playing a pivotal role as a potent mediator of the leukotriene (Lts) inflammatory pathway. Nordihydroguaiaretic acid (NDGA) functions as a natural orthosteric inhibitor of 5LOX, while 3-acetyl-11-keto-β-boswellic acid (AKBA) acts as a natural allosteric inhibitor targeting 5LOX. However, the precise mechanisms of inhibition have remained unclear. In this study, Gaussian accelerated molecular dynamics (GaMD) simulation was employed to elucidate the inhibitory mechanisms of NDGA and AKBA on 5LOX. It was found that the orthosteric inhibitor NDGA was tightly bound in the protein's active pocket, occupying the active site and inhibiting the catalytic activity of the 5LOX enzyme through competitive inhibition. The binding of the allosteric inhibitor AKBA induced significant changes at the distal active site, leading to a conformational shift of residues 168-173 from a loop to an α-helix and significant negative correlated motions between residues 285-290 and 375-400, reducing the distance between these segments. In the simulation, the volume of the active cavity in the stable conformation of the protein was reduced, hindering the substrate's entry into the active cavity and, thereby, inhibiting protein activity through allosteric effects. Ultimately, Markov state models (MSM) were used to identify and classify the metastable states of proteins, revealing the transition times between different conformational states. In summary, this study provides theoretical insights into the inhibition mechanisms of 5LOX by AKBA and NDGA, offering new perspectives for the development of novel inhibitors specifically targeting 5LOX, with potential implications for anti-inflammatory drug development.

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.

Activation of Polycystin-1 Signaling by Binding of Stalk-derived Peptide Agonists.

Polycystin-1 (PC1) is the membrane protein product of the PKD1 gene whose mutation is responsible for 85% of the cases of autosomal dominant polycystic kidney disease (ADPKD). ADPKD is primarily characterized by the formation of renal cysts and potential kidney failure. PC1 is an atypical G protein-coupled receptor (GPCR) consisting of 11 transmembrane helices and an autocatalytic GAIN domain that cleaves PC1 into extracellular N-terminal (NTF) and membrane-embedded C-terminal (CTF) fragments. Recently, signaling activation of the PC1 CTF was shown to be regulated by a stalk tethered agonist (TA), a distinct mechanism observed in the adhesion GPCR family. A novel allosteric activation pathway was elucidated for the PC1 CTF through a combination of Gaussian accelerated molecular dynamics (GaMD), mutagenesis and cellular signaling experiments. Here, we show that synthetic, soluble peptides with 7 to 21 residues derived from the stalk TA, in particular, peptides including the first 9 residues (p9), 17 residues (p17) and 21 residues (p21) exhibited the ability to re-activate signaling by a stalkless PC1 CTF mutant in cellular assays. To reveal molecular mechanisms of stalk peptide-mediated signaling activation, we have applied a novel Peptide GaMD (Pep-GaMD) algorithm to elucidate binding conformations of selected stalk peptide agonists p9, p17 and p21 to the stalkless PC1 CTF. The simulations revealed multiple specific binding regions of the stalk peptide agonists to the PC1 protein including an "intermediate" bound yet inactive state. Our Pep-GaMD simulation findings were consistent with the cellular assay experimental data. Binding of peptide agonists to the TOP domain of PC1 induced close TOP-putative pore loop interactions, a characteristic feature of the PC1 CTF signaling activation mechanism. Using sequence covariation analysis of PC1 homologs, we further showed that the peptide binding regions were consistent with covarying residue pairs identified between the TOP domain and the stalk TA. Therefore, structural dynamic insights into the mechanisms of PC1 activation by stalk-derived peptide agonists have enabled an in-depth understanding of PC1 signaling. They will form a foundation for development of PC1 as a therapeutic target for the treatment of ADPKD.

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.

Unveiling Conformational States of CDK6 Caused by Binding of Vcyclin Protein and Inhibitor by Combining Gaussian Accelerated Molecular Dynamics and Deep Learning.

CDK6 plays a key role in the regulation of the cell cycle and is considered a crucial target for cancer therapy. In this work, conformational transitions of CDK6 were identified by using Gaussian accelerated molecular dynamics (GaMD), deep learning (DL), and free energy landscapes (FELs). DL finds that the binding pocket as well as the T-loop binding to the Vcyclin protein are involved in obvious differences of conformation contacts. This result suggests that the binding pocket of inhibitors (LQQ and AP9) and the binding interface of CDK6 to the Vcyclin protein play a key role in the function of CDK6. The analyses of FELs reveal that the binding pocket and the T-loop of CDK6 have disordered states. The results from principal component analysis (PCA) indicate that the binding of the Vcyclin protein affects the fluctuation behavior of the T-loop in CDK6. Our QM/MM-GBSA calculations suggest that the binding ability of LQQ to CDK6 is stronger than AP9 with or without the binding of the Vcyclin protein. Interaction networks of inhibitors with CDK6 were analyzed and the results reveal that LQQ contributes more hydrogen binding interactions (HBIs) and hot interaction spots with CDK6. In addition, the binding pocket endures flexibility changes from opening to closing states and the Vcyclin protein plays an important role in the stabilizing conformation of the T-loop. We anticipate that this work could provide useful information for further understanding the function of CDK6 and developing new promising inhibitors targeting CDK6.

The binding pattern of ferric iron and iron-binding protein in Botrytis cinerea

Iron-binding protein (Ibp) has protective effect on pathogen exposed to H2O2 in defense response of plants. Ibp in Botrytis cinerea (BcIbp) is related to its virulence. Bcibp mutation lead to virulence deficiencies in B. cinerea. BcIbp is involved in the Fe3+ homeostasis regulation. Recognition the binding site and binding pattern of ferric iron and iron-binding protein in B. cinerea are vital to understand its function. In this study, molecular dynamics (MD) simulations, gaussian accelerated molecular dynamics (GaMD) simulations, dynamic cross correlation analysis and quantum chemical energy calculation were used to explore binding pattern of ferric iron. MD results showed that the C-terminal region had little effect on the stability of residues in the Fe3+-binding pocket. Energy calculations suggested the most likely coordination pattern for ferric iron in iron-binding protein. These results will help to understand the binding of ferric iron to iron-binding protein and provide new ideas for regulating the virulence of B. cinerea.

Molecular Mechanism of Phosphorylation-Mediated Impacts on the Conformation Dynamics of GTP-Bound KRAS Probed by GaMD Trajectory-Based Deep Learning.

The phosphorylation of different sites produces a significant effect on the conformational dynamics of KRAS. Gaussian accelerated molecular dynamics (GaMD) simulations were combined with deep learning (DL) to explore the molecular mechanism of the phosphorylation-mediated effect on conformational dynamics of the GTP-bound KRAS. The DL finds that the switch domains are involved in obvious differences in conformation contacts and suggests that the switch domains play a key role in the function of KRAS. The analyses of free energy landscapes (FELs) reveal that the phosphorylation of pY32, pY64, and pY137 leads to more disordered states of the switch domains than the wild-type (WT) KRAS and induces conformational transformations between the closed and open states. The results from principal component analysis (PCA) indicate that principal motions PC1 and PC2 are responsible for the closed and open states of the phosphorylated KRAS. Interaction networks were analyzed and the results verify that the phosphorylation alters interactions of GTP and magnesium ion Mg2+ with the switch domains. It is concluded that the phosphorylation pY32, pY64, and pY137 tune the activity of KRAS through changing conformational dynamics and interactions of the switch domains. We anticipated that this work could provide theoretical aids for deeply understanding the function of KRAS.

Elucidating the structural basis of vitamin B12 derivatives as novel potent inhibitors of PTP1B: Insights from inhibitory mechanisms using Gaussian accelerated molecular dynamics (GaMD) and in vitro study

Vitamin B12 is a group of biologically active cobalamin compounds. In this study, we investigated the inhibitory effects of methylcobalamin (MeCbl) and hydroxocobalamin acetate (OHCbl Acetate) on protein tyrosine phosphatase 1B (PTP1B). MeCbl and OHCbl Acetate exhibited an IC50 of approximately 58.390 ± 2.811 μM and 8.998 ± 0.587 μM, respectively. The Ki values of MeCbl and OHCbl Acetate were 25.01 μM and 4.04 μM respectively. To elucidate the inhibition mechanism, we conducted a 500 ns Gaussian accelerated molecular dynamics (GaMD) simulation. Utilizing PCA and tICA, we constructed Markov state models (MSM) to examine secondary structure changes during motion. Our findings revealed that the α-helix at residues 37–42 remained the most stable in the PTP1B-OHCbl Acetate system. Furthermore, upon binding of OHCbl Acetate or MeCbl, the WPD loop of PTP1B moved inward to the active pocket, forming a closed conformation and potentially obstructs substrate entry. Protein-ligand interaction analysis and MM-PBSA showed that OHCbl Acetate exhibited lower binding free energy and engaged in more residue interactions with PTP1B. In summary, our study confirmed the substantial inhibitory activity of OHCbl Acetate against PTP1B, with its inhibitory potency notably surpassing that of MeCbl. We demonstrated potential molecular mechanisms of OHCbl Acetate inhibiting PTP1B.

Gaussian accelerated molecular dynamics simulations facilitate prediction of the permeability of cyclic peptides.

Despite their widespread use as therapeutics, clinical development of small molecule drugs remains challenging. Among the many parameters that undergo optimization during the drug development process, increasing passive cell permeability (i.e., log(P)) can have some of the largest impact on potency. Cyclic peptides (CPs) have emerged as a viable alternative to small molecules, as they retain many of the advantages of small molecules (oral availability, target specificity) while being highly effective at traversing the plasma membrane. However, the relationship between the dominant conformations that typify CPs in an aqueous versus a membrane environment and cell permeability remain poorly characterized. In this study, we have used Gaussian accelerated molecular dynamics (GaMD) simulations to characterize the effect of solvent on the free energy landscape of lariat peptides, a subset of CPs that have recently shown potential for drug development (Kelly et al., JACS 2021). Differences in the free energy of lariat peptides as a function of solvent can be used to predict permeability of these molecules, and our results show that permeability is most greatly influenced by N-methylation and exposure to solvent. Our approach lays the groundwork for using GaMD as a way to virtually screen large libraries of CPs and drive forward development of CP-based therapeutics.

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.

Computational insights into diverse binding modes of the allosteric modulator and their regulation on dopamine D1 receptor

Allosteric drugs hold the promise of addressing many challenges in the current drug development of GPCRs. However, the molecular mechanism underlying their allosteric modulations remain largely elusive. The dopamine D1 receptor (DRD1), a member of Class A GPCRs, is critical for treating psychiatric disorders, and LY3154207 serves as its promising positive allosteric modulator (PAM). In the work, we utilized extensive Gaussian-accelerated molecular dynamics simulations (a total of 41μs) for the first time probe the diverse binding modes of the allosteric modulator and their regulation effects, based on the DRD1 and LY3154207 as representative. Our simulations identify four binding modes of LY3154207 (one boat mode, two metastable vertical modes and a novel cleft-anchored mode), in which the boat mode is the most stable while there three modes are similar in the stability. However, it is interesting to observed that the most stable boat mode inversely exhibits the weakest positive allosteric effect on influencing the orthosteric ligand binding and maintaining the activity of the transducer binding site. It should result from its induced weaker correlation between the allosteric site and the orthosteric site, and between the orthosteric site and the transducer binding site than the other three binding modes, as well as its weakened interaction between a crucial activation-related residue (S2025.46) and the orthosteric ligand (dopamine). Overall, the work offers atomic-level information to advance our understanding of the complex allosteric regulation on GPCRs, which is beneficial to the allosteric modulator design and development.

Mutations influence the conformational dynamics of the GDP/KRAS complex

Mutations near allosteric sites can have a significant impact on the function of KRAS. Three specific mutations, K104Q, G12D/K104Q, and G12D/G75A, which are located near allosteric positions, were selected to investigate the molecular mechanisms behind mutation-induced influences on the activity of KRAS. Gaussian accelerated molecular dynamics (GaMD) simulations followed by the principal component analysis (PCA) were performed to improve the sampling of conformational states. The results revealed that these mutations significantly alter the structural flexibility, correlated motions, and dynamic behavior of the switch regions that are essential for KRAS binding to effectors or regulators. Furthermore, the mutations have a significant impact on the hydrogen bonding interactions between GDP and the switch regions, as well as on the electrostatic interactions of magnesium ions (Mg2+) with these regions. Our results verified that these mutations strongly influence the binding of KRAS to its effectors or regulators and allosterically regulate the activity. We believe that this work can provide valuable theoretical insights into a deeper understanding of KRAS function. Communicated by Ramaswamy H. Sarma