Unbiased Molecular Dynamics Simulations Research Articles

Free energy landscape of the PI3Kα C-terminal activation

The gene PIK3CA, encoding the catalytic subunit p110α of PI3Kα, is the second most frequently mutated gene in cancer, with the highest frequency oncogenic mutants occurring in the C-terminus of the kinase domain. The C-terminus has a dual function in regulating the kinase, playing a putative auto-inhibitory role for kinase activity and being absolutely essential for binding to the cell membrane. However, the molecular mechanisms by which these C-terminal oncogenic mutations cause PI3Kα overactivation remain unclear. To understand how a spectrum of C-terminal mutations of PI3Kα alter kinase activity compared to the WT, we perform unbiased and biased Molecular Dynamics simulations of several C-terminal mutants and report the free energy landscapes for the C-terminal “closed-to-open” transition in the WT, H1047R, G1049R, M1043L and N1068KLKR mutants. Results are consistent with HDX-MS experimental data and provide a molecular explanation why H1047R and G1049R reorient the C-terminus with a different mechanism compared to the WT and M1043L and N1068KLKR mutants. Moreover, we show that in the H1047R mutant, the cavity, where the allosteric ligands STX-478 and RLY-2608 bind, is more accessible contrary to the WT. This study provides insights into the molecular mechanisms underlying activation of oncogenic PI3Kα by C-terminal mutations and represents a valuable resource for continued efforts in the development of mutant selective inhibitors as therapeutics.

Abstract PO3-26-09: A novel class of RNR inhibitors that induces genomic instability and breast cancer cell death without inducing overt toxicities

Abstract Despite the development of screening techniques and therapies, nearly 30% of breast cancers progress to Stage IV metastatic disease. These advanced cancers are highly proliferative, engaging in ongoing DNA synthesis that requires ribonucleotide reductase (RNR), the rate-limiting enzyme for dNTP synthesis. RRM2, the small subunit of RNR, activates the enzyme, increases deoxynucleotide pools, and is overexpressed in many cancers, including breast cancer. Thus, RNR is an established therapeutic target in advanced breast cancer. Currently, gemcitabine is the only FDA-approved RNR inhibitor used to treat Stage IV disease. As a nucleoside analog, gemcitabine also causes severe dose-limiting toxicities (i.e. myelosuppression and hepatotoxicity) due to off-target DNA replication termination. We hypothesize that a novel, non-nucleoside, RNR inhibitor may overcome these limitations. To address this, we developed TMU27a, a derivative of naphthyl salicylic acyl hydrazone (NSAH), which was identified in an in silico screen for its high-affinity binding to the RNR catalytic site. To measure direct interactions between TMU27a and purified RNR protein, we used surface plasmon resonance, revealing on-target, tight binding (Kd = 150 nM). Unbiased docking and molecular dynamics simulations (using lowest energy calculations) predicted the binding sight of TMU27a to be the catalytic site of RNR, where it is stabilized through extensive interactions formed with conserved residues. Preliminary docking predictions also indicate multiple clash sites between TMU27a and the DNA polymerase lambda nucleotide pocket even in the lowest energy pose (unlike gemcitabine), suggesting that TMU27a inhibits RNR activity through a novel mechanism without significant off-target binding to other nucleotide binding proteins that contribute to toxicity. Demonstrating on-target inhibition, TMU27a reduces dATP levels and induces S and G2/M-phase stalling, leading to significant DNA damage and chromosomal instability. This excessive genomic damage causes growth repression, apoptosis, and senescence in several triple negative breast cancer (TNBC) cell lines. In xenograft mouse models of TNBC, TMU27a fully suppressed tumor growth without impacting mouse weight, suggesting strong drug efficacy in the absence of overt toxicity. Moreover, while short-term exposure to gemcitabine suppresses red and white blood cell populations, TMU27a does not. Together, these data indicate that TMU27a and its potential analogs are novel, non-toxic RNR inhibitors that overcome the limitations of gemcitabine for treating breast cancer. We are currently investigating how and where TMU27a binds human RNR using cryo-electron microscopy with the goal of generating a novel class of RNR inhibitors through structure-based drug design, improving binding affinity and selectivity. Citation Format: Taylor Baker, Kristen Weber-Bonk, Wei Huang, Derek Taylor, Ruth Keri. A novel class of RNR inhibitors that induces genomic instability and breast cancer cell death without inducing overt toxicities [abstract]. In: Proceedings of the 2023 San Antonio Breast Cancer Symposium; 2023 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2024;84(9 Suppl):Abstract nr PO3-26-09.

Extracting binding energies and binding modes from biomolecular simulations of fragment binding to endothiapepsin.

Fragment-based drug discovery (FBDD) aims to discover a set of small binding fragments that may be subsequently linked together. Therefore, in-depth knowledge of the individual fragments' structural and energetic binding properties is essential. In addition to experimental techniques, the direct simulation of fragment binding by molecular dynamics (MD) simulations became popular to characterize fragment binding. However, former studies showed that long simulation times and high computational demands per fragment are needed, which limits applicability in FBDD. Here, we performed short, unbiased MD simulations of direct fragment binding to endothiapepsin, a well-characterized model system of pepsin-like aspartic proteases. To evaluate the strengths and limitations of short MD simulations for the structural and energetic characterization of fragment binding, we predicted the fragments' absolute free energies and binding poses based on the direct simulations of fragment binding and compared the predictions to experimental data. The predicted absolute free energies are in fair agreement with the experiment. Combining the MD data with binding mode predictions from molecular docking approaches helped to correctly identify the most promising fragments for further chemical optimization. Importantly, all computations and predictions were done within 5 days, suggesting that MD simulations may become a viable tool in FBDD projects.

Unlocking the specificity of antimicrobial peptide interactions for membrane-targeted therapies

Antimicrobial peptides (AMPs) are increasingly recognized as potent therapeutic agents, with their selective affinity for pathological membranes, low toxicity profile, and minimal resistance development making them particularly attractive in the pharmaceutical landscape. This study offers a comprehensive analysis of the interaction between specific AMPs, including magainin-2, pleurocidin, CM15, LL37, and clavanin, with lipid bilayer models of very different compositions that have been ordinarily used as biological membrane models of healthy mammal, cancerous, and bacterial cells. Employing unbiased molecular dynamics simulations and metadynamics techniques, we have deciphered the intricate mechanisms by which these peptides recognize pathogenic and pathologic lipid patterns and integrate into lipid assemblies. Our findings reveal that the transverse component of the peptide's hydrophobic dipole moment is critical for membrane interaction, decisively influencing the molecule's orientation and expected therapeutic efficacy. Our approach also provides insight on the kinetic and dynamic dependence on the peptide orientation in the axial and azimuthal angles when coming close to the membrane. The aim is to establish a robust framework for the rational design of peptide-based, membrane-targeted therapies, as well as effective quantitative descriptors that can facilitate the automated design of novel AMPs for these therapies using machine learning methods.

Mechanistic insights into G-protein activation via phosphorylation mediated non-canonical pathway

Activation of heterotrimeric G-proteins (Gαβγ) downstream to receptor tyrosine kinases (RTKs) is a well-established crosstalk between the signaling pathways mediated by G-protein coupled receptors (GPCRs) and RTKs. While GPCR serves as a guanine exchange factor (GEF) in the canonical activation of Gα that facilitates the exchange of GDP for GTP, the mechanism through which RTK phosphorylations induce Gα activation remains unclear. Recent experimental studies revealed that the epidermal growth factor receptor (EGFR), a well-known RTK, phosphorylates the helical domain tyrosine residues Y154 and Y155 and accelerates the GDP release from the Gαi3, a subtype of Gα-protein. Using well-tempered metadynamics and extensive unbiased molecular dynamics simulations, we captured the GDP release event and identified the intermediates between bound and unbound states through Markov state models. In addition to weakened salt bridges at the domain interface, phosphorylations induced the unfolding of helix αF, which contributed to increased flexibility near the hinge region, facilitating a greater distance between domains in the phosphorylated Gαi3. Although the larger domain separation in the phosphorylated system provided an unobstructed path for the nucleotide, the accelerated release of GDP was attributed to increased fluctuations in several conserved regions like P-loop, switch 1, and switch 2. Overall, this study provides atomistic insights into the activation of G-proteins induced by RTK phosphorylations and identifies the specific structural motifs involved in the process. The knowledge gained from the study could establish a foundation for targeting non-canonical signaling pathways and developing therapeutic strategies against the ailments associated with dysregulated G-protein signaling.

Molecular Mechanisms Underlying Medium-Chain Free Fatty Acid-Regulated Activity of the Phospholipase PlaF from Pseudomonas aeruginosa.

PlaF is a membrane-bound phospholipase A1 from Pseudomonas aeruginosa that is involved in remodeling membrane glycerophospholipids (GPLs) and modulating virulence-associated signaling and metabolic pathways. Previously, we identified the role of medium-chain free fatty acids (FFAs) in inhibiting PlaF activity and promoting homodimerization, yet the underlying molecular mechanism remained elusive. Here, we used unbiased and biased molecular dynamics simulations and free energy computations to assess how PlaF interacts with FFAs localized in the water milieu surrounding the bilayer or within the bilayer and how these interactions regulate PlaF activity. Medium-chain FFAs localized in the upper bilayer leaflet can stabilize inactive dimeric PlaF, likely through interactions with charged surface residues, as has been experimentally validated. Potential of mean force (PMF) computations indicate that membrane-bound FFAs may facilitate the activation of monomeric PlaF by lowering the activation barrier for changing into a tilted, active configuration. We estimated that the coupled equilibria of PlaF monomerization-dimerization and tilting at the physiological concentration of PlaF lead to the majority of PlaF forming inactive dimers when in a cell membrane loaded with decanoic acid (C10). This is in agreement with a suggested in vivo product feedback loop and gas chromatography-mass spectrometry profiling results, indicating that PlaF catalyzes the release of C10 from P. aeruginosa membranes. Additionally, we found that C10 in the water milieu can access the catalytic site of active monomeric PlaF, contributing to the competitive component of C10-mediated PlaF inhibition. Our study provides mechanistic insights into how medium-chain FFAs may regulate the activity of PlaF, a potential bacterial drug target.

Tepotinib and tivantinib as potential inhibitors for the serine/threonine kinase of the mpox virus: insights from structural bioinformatics analysis

The serine/threonine kinase (STK) plays a central role as the primary kinase in poxviruses, directing phosphoryl transfer reactions. Such reactions are pivotal for the activation of certain proteins during viral replication, assembly, and maturation. Therefore, targeting this key protein is anticipated to impede virus replication. In this work, a structural bioinformatics approach was employed to evaluate the potential of drug-like kinase inhibitors in binding to the ATP-binding pocket on the STK of the Mpox virus. Virtual screening of known kinase inhibitors revealed that the top 10 inhibitors exhibited binding affinities ranging from −8.59 to −12.05 kcal/mol. The rescoring of compounds using the deep-learning default model in GNINA was performed to predict accurate binding poses. Subsequently, the top three inhibitors underwent unbiased molecular dynamics (MD) simulations for 100 ns. Molecular Mechanics/Generalized Born Surface Area (MM/GBSA) analysis and Principal Component Analysis (PCA) suggested tepotinib as a competitive inhibitor for Mpox virus STK as evidenced by its binding free energy and the induction of similar conformational behavior of the enzyme. Nevertheless, it is sensible to experimentally test all top 10 compounds, as scoring functions and energy calculations may not consistently align with experimental findings. These insights are poised to provide an attempt to identify an effective inhibitor for the Mpox virus. Communicated by Ramaswamy H. Sarma

Free energy profile of the substrate-induced occlusion of the human serotonin transporter.

The serotonin transporter (SERT) is a member of the Solute Carrier 6 (SLC6) family and is responsible for maintaining the appropriate level of serotonin in the brain. Dysfunction of SERT has been linked to several neuropsychiatric disorders, including depression, anxiety and obsessive-compulsive disorder. Therefore, an in-depth understanding of the mechanism on an atomistic level, coupled with a quantification of transporter dynamics and the associated free energies is required. Here, we constructed Markov state models (MSMs) from extensive unbiased molecular dynamics simulations to quantify the free energy profile of serotonin (5HT) triggered SERT occlusion and explored the driving forces of the mechanism of occlusion. Our results reveal that SERT occludes via multiple intermediate conformations and show that the motion of occlusion is energetically downhill for the 5HT-bound transporter. Force distribution analyses show that the interactions of 5HT with the bundle domain are crucial. During occlusion, attractive forces steadily increase and pull on the bundle domain, which leads to SERT occlusion. Some interactions become repulsive upon full occlusion, suggesting that SERT creates pressure on 5HT to promote its movement towards the cytosol.

Therapeutic Peptides Are Preferentially Solubilized in Specific Microenvironments within PEG-PLGA Polymer Nanoparticles.

Polymeric nanoparticles are a highly promising drug delivery formulation. However, a lack of understanding of the molecular mechanisms that underlie their drug solubilization and controlled release capabilities has hindered the efficient clinical translation of such technologies. Polyethylene glycol-poly(lactic-co-glycolic) acid (PEG-PLGA) nanoparticles have been widely studied as cancer drug delivery vehicles. In this letter, we use unbiased coarse-grained molecular dynamics simulations to model the self-assembly of a PEG-PLGA nanoparticle and its solubulization of the anticancer peptide, EEK, with good agreement with previously reported experimental structural data. We applied unsupervised machine learning techniques to quantify the conformations that polymers adopt at various locations within the nanoparticle. We find that the local microenvironments formed by the various polymer conformations promote preferential EEK solubilization within specific regions of the NP. This demonstrates that these microenvironments are key in controlling drug storage locations within nanoparticles, supporting the rational design of nanoparticles for therapeutic applications.

Binding of Cholesterol to the N-Terminal Domain of the NPC1L1 Transporter: Analysis of the Epimerization-Related Binding Selectivity and Loop Mutations.

Cholesterol is a fat-like substance with a pivotal physiological relevance in humans, and its homeostasis is tightly regulated by various cellular processes, including the import in the small intestine and the reabsorption in the biliary ducts by the Niemann-Pick C1 Like 1 (NPC1L1) importer. NPC1L1 can mediate the absorption of a variety of sterols but strikingly exhibits a large sensitivity to cholesterol epimerization. This study examines the molecular basis of the epimerization-related selective binding of cholesterol by combining extended unbiased molecular dynamics simulations of the apo and holo species of the N-terminal domain of wild-type NPC1L1, in conjunction with relative binding free energy, umbrella sampling, and well-tempered metadynamics calculations. The analysis of the results discloses the existence of two distinct binding modes for cholesterol and epi-cholesterol. The former binds deeper in the cavity, forming key hydrogen-bond interactions with Q95, S56, and a water molecule. In contrast, epi-cholesterol is shifted ca. 3 Å to the mouth of the cavity and the transition to the Q95 site is prevented by an energetic barrier of 4.1 kcal·mol-1. Thus, the configuration of the hydroxyl group of cholesterol, together with the presence of a structural water molecule, is a key feature for effective absorption. Finally, whereas these findings may seemingly be challenged by single-point mutations that impair cholesterol transport but have a mild impact on the binding of cholesterol to the Q95 binding site, our results reveal that they have a drastic influence on the conformational landscape of the α8/β7 loop in the apo species compared to the wild-type protein. Overall, the results give support to the functional role played by the α8/β7 loop in regulating the access of ligands to NPC1L1, and hence to interpreting the impact of these mutations on diseases related to disruption of sterol absorption, paving the way to understanding certain physiological dysfunctions.

Decrypting Allostery in Membrane-Bound K-Ras4B Using Complementary In Silico Approaches Based on Unbiased Molecular Dynamics Simulations.

Protein functions are dynamically regulated by allostery, which enables conformational communication even between faraway residues, and expresses itself in many forms, akin to different "languages": allosteric control pathways predominating in an unperturbed protein are often unintuitively reshaped whenever biochemical perturbations arise (e.g., mutations). To accurately model allostery, unbiased molecular dynamics (MD) simulations require integration with a reliable method able to, e.g., detect incipient allosteric changes or likely perturbation pathways; this is because allostery can operate at longer time scales than those accessible by plain MD. Such methods are typically applied singularly, but we here argue their joint application─as a "multilingual" approach─could work significantly better. We successfully prove this through unbiased MD simulations (∼100 μs) of the widely studied, allosterically active oncotarget K-Ras4B, solvated and embedded in a phospholipid membrane, from which we decrypt allostery using four showcase "languages": Distance Fluctuation analysis and the Shortest Path Map capture allosteric hotspots at equilibrium; Anisotropic Thermal Diffusion and Dynamical Non-Equilibrium MD simulations assess perturbations upon, respectively, either superheating or hydrolyzing the GTP that oncogenically activates K-Ras4B. Chosen "languages" work synergistically, providing an articulate, mutually coherent, experimentally consistent picture of K-Ras4B allostery, whereby distinct traits emerge at equilibrium and upon GTP cleavage. At equilibrium, combined evidence confirms prominent allosteric communication from the membrane-embedded hypervariable region, through a hub comprising helix α5 and sheet β5, and up to the active site, encompassing allosteric "switches" I and II (marginally), and two proposed pockets. Upon GTP cleavage, allosteric perturbations mostly accumulate on the switches and documented interfaces.

Deciphering insights into the binding mechanism and plasticity of Telacebec with M. tuberculosis cytochrome bcc-aa3 supercomplex through an unbiased molecular dynamics simulation, free-energy analysis, and DFT study

The cytochrome bcc-aa3 supercomplex, a key component in the electron transport chain pathway involved in bacterial energy production and homeostasis, is a clinically validated target for tuberculosis (TB), leading to Telacebec (Q203). Telacebec is a potent candidate drug under Phase II clinical development for the treatment of drug-sensitive and drug-resistant TB. Recently, the cryo-electron microscopy structure of this supercomplex from Mycobacterium tuberculosis (Mtb) complexed with Q203 was resolved at 6.9 Å resolution (PDB ID: 7E1W). To understand the binding site (QP site) flexibility and Q203’s stability at the QP site of the Mtb cytochrome bcc complex, we conducted molecular dynamics (MD) simulation and free energy analysis on this complex in an explicit hydrated lipid bilayer environment for 500 ns. Through this study, the persistence of a range of direct and indirect interactions was observed over the course of the simulation. The significance of the interactions with His375, Tyr161, Ala178, Ala179, Ile183, His355, Leu356, and Thr313 is underlined. Electrostatic energy was the primary source of the net binding free energy, regardless of the important interacting residues. The overall binding free energy for Q203 was −112.84 ± 7.73 kcal/mol, of which the electrostatic and lipophilic energy contributions were −116.31 ± 1.14 and −21.32 ± 2.35 kcal/mol, respectively. Meanwhile, DFT calculations were utilized to elucidate Q203’s molecular properties. Overall, this study deciphers key insights into the cytochrome bcc-aa3 supercomplex with Q203 on the ground of molecular mechanics and quantum mechanics that may facilitate structure-based drug design and optimization for the discovery of the next-generation antitubercular drug(s). Communicated by Ramaswamy H. Sarma

Dynamics behavior of PE and PET oligomers in lipid bilayer simulations

In recent years many investigators have been concerned about the toxicity and potential health hazards of micro- and nanoplastics. However, we are still lacking a good understanding of the methods of their transport into the human body and subsequently within cells. This is especially true at the lower nanometer scale; these particles are potentially more dangerous than their micrometer counterparts due to their easier permeation into cells. In this study we used both unbiased molecular dynamics simulations and steered umbrella sampling simulations to explore the interactions of polyethylene terephthalate (PET) and polyethylene (PE) oligomers in phospholipid bilayers. Our simulations revealed that the bilayers did not represent significant energy barriers to the small oligomers; not only did they readily enter the cell membrane but they also became concentrated into specific parts of the membrane. The larger PET tetramers exhibited a strong aggregation in water but were the least likely to permeate through or into the membranes. It is possible that PE monomers and tetramers can become concentrated into membranes while PET monomers are more likely to pass through or concentrate just inside the membrane surface. Passive transport of microplastics into cells is, however, likely limited to particles of a few nanometers in diameter.

Unveiling local and global conformational changes and allosteric communications in SOD1 systems using molecular dynamics simulation and network analyses

BackgroundAmyotrophic lateral sclerosis (ALS) is a serious neurodegenerative disorder affecting nerve cells in the brain and spinal cord that is caused by mutations in the superoxide dismutase 1 (SOD1) enzyme. ALS-related mutations cause misfolding, dimerisation instability, and increased formation of aggregates. The underlying allosteric mechanisms, however, remain obscure as far as details of their fundamental atomistic structure are concerned. Hence, this gap in knowledge limits the development of novel SOD1 inhibitors and the understanding of how disease-associated mutations in distal sites affect enzyme activity.Methods: We combined microsecond-scale based unbiased molecular dynamics (MD) simulation with network analysis to elucidate the local and global conformational changes and allosteric communications in SOD1 Apo (unmetallated form), Holo, Apo_CallA (mutant and unmetallated form), and Holo_CallA (mutant form) systems. To identify hotspot residues involved in SOD1 signalling and allosteric communications, we performed network centrality, community network, and path analyses.Results: Structural analyses showed that unmetallated SOD1 systems and cysteine mutations displayed large structural variations in the catalytic sites, affecting structural stability. Inter- and intra H-bond analyses identified several important residues crucial for maintaining interfacial stability, structural stability, and enzyme catalysis. Dynamic motion analysis demonstrated more balanced atomic displacement and highly correlated motions in the Holo system. The rationale for structural disparity observed in the disulfide bond formation and R143 configuration in Apo and Holo systems were elucidated using distance and dihedral probability distribution analyses.Conclusion: Our study highlights the efficiency of combining extensive MD simulations with network analyses to unravel the features of protein allostery.

Passive permeability controls synthesis for the allelochemical sorgoleone in sorghum root exudate

Competition for soil nutrients and water with other plants foster competition within the biosphere for access to these limited resources. The roots for the common grain sorghum produce multiple small molecules that are released via root exudates into the soil to compete with other plants. Sorgoleone is one such compound, which suppresses weed growth near sorghum by acting as a quinone analog and interferes with photosynthesis. Since sorghum also grows photosynthetically, and may be susceptible to sorgoleone action if present in tissues above ground, it is essential to exude sorgoleone efficiently. However, since the P450 enzymes that synthesize sorgoleone are intracellular, the release mechanism for sorgoleone remain unclear. In this study, we conducted an in silico assessment for sorgoleone and its precursors to passively permeate biological membranes. To facilitate accurate simulation, CHARMM parameters were newly optimized for sorgoleone and its precursors. These parameters were used to conduct 1 μs of unbiased molecular dynamics simulations to compare the permeability of sorgoleone with its precursors molecules. We find that interleaflet transfer is maximized for sorgoleone, suggesting that the precursor molecules may remain in the same leaflet for access by biosynthetic P450 enzymes. Since no sorgoleone was extracted during unbiased simulations, we compute a permeability coefficient using the inhomogeneous solubility diffusion model. The requisite free energy and diffusivity profiles for sorgoleone through a sorghum membrane model were determined through Replica Exchange Umbrella Sampling (REUS) simulations. The REUS calculations highlight that any soluble sorgoleone would quickly insert into a lipid bilayer, and would readily transit. When sorgoleone forms aggregates in root exudate as indicated by our equilibrium simulations, aggregate formation would lower the effective concentration in aqueous solution, creating a concentration gradient that would facilitate passive transport. This suggests that sorgoleone synthesis occurs within sorghum root cells and that sorgoleone is exuded by permeating through the cell membrane without the need for a transport protein once the extracellular sorgoleone aggregate is formed.

Machine learning coarse-grained potentials of protein thermodynamics

A generalized understanding of protein dynamics is an unsolved scientific problem, the solution of which is critical to the interpretation of the structure-function relationships that govern essential biological processes. Here, we approach this problem by constructing coarse-grained molecular potentials based on artificial neural networks and grounded in statistical mechanics. For training, we build a unique dataset of unbiased all-atom molecular dynamics simulations of approximately 9 ms for twelve different proteins with multiple secondary structure arrangements. The coarse-grained models are capable of accelerating the dynamics by more than three orders of magnitude while preserving the thermodynamics of the systems. Coarse-grained simulations identify relevant structural states in the ensemble with comparable energetics to the all-atom systems. Furthermore, we show that a single coarse-grained potential can integrate all twelve proteins and can capture experimental structural features of mutated proteins. These results indicate that machine learning coarse-grained potentials could provide a feasible approach to simulate and understand protein dynamics.

Molecular Dynamics Simulations of the Human Ecto-5'-Nucleotidase (h-ecto-5'-NT, CD73): Insights into Protein Flexibility and Binding Site Dynamics.

Human ecto-5'-nucleotidase (h-ecto-5'-NT, CD73) is a homodimeric Zn2+-binding metallophosphoesterase that hydrolyzes adenosine 5'-monophosphate (5'-AMP) to adenosine and phosphate. h-Ecto-5'-NT is a key enzyme in purinergic signaling pathways and has been recognized as a promising biological target for several diseases, including cancer and inflammatory, infectious, and autoimmune diseases. Despite its importance as a biological target, little is known about h-ecto-5'-NT dynamics, which poses a considerable challenge to the design of inhibitors of this target enzyme. Here, to explore h-ecto-5'-NT flexibility, all-atom unbiased molecular dynamics (MD) simulations were performed. Remarkable differences in the dynamics of the open (catalytically inactive) and closed (catalytically active) conformations of the apo-h-ecto-5'-NT were observed during the simulations, and the nucleotide analogue inhibitor AMPCP was shown to stabilize the protein structure in the closed conformation. Our results suggest that the large and complex domain motion that enables the h-ecto-5'-NT open/closed conformational switch is slow, and therefore, it could not be completely captured within the time scale of our simulations. Nonetheless, we were able to explore the faster dynamics of the h-ecto-5'-NT substrate binding site, which is mainly located at the C-terminal domain and well conserved among the protein's open and closed conformations. Using the TRAPP ("Transient Pockets in Proteins") approach, we identified transient subpockets close to the substrate binding site. Finally, conformational states of the substrate binding site with higher druggability scores than the crystal structure were identified. In summary, our study provides valuable insights into h-ecto-5'-NT structural flexibility, which can guide the structure-based design of novel h-ecto-5'-NT inhibitors.

Autoencoders for dimensionality reduction in molecular dynamics: Collective variable dimension, biasing, and transition states.

The heat shock protein 90 (Hsp90) is a molecular chaperone that controls the folding and activation of client proteins using the free energy of ATP hydrolysis. The Hsp90 active site is in its N-terminal domain (NTD). Our goal is to characterize the dynamics of NTD using an autoencoder-learned collective variable (CV) in conjunction with adaptive biasing force Langevin dynamics. Using dihedral analysis, we cluster all available experimental Hsp90 NTD structures into distinct native states. We then perform unbiased molecular dynamics (MD) simulations to construct a dataset that represents each state and use this dataset to train an autoencoder. Two autoencoder architectures are considered, with one and two hidden layers, respectively, and bottlenecks of dimension k ranging from 1 to 10. We demonstrate that the addition of an extra hidden layer does not significantly improve the performance, while it leads to complicated CVs that increase the computational cost of biased MD calculations. In addition, a two-dimensional (2D) bottleneck can provide enough information of the different states, while the optimal bottleneck dimension is five. For the 2D bottleneck, the 2D CV is directly used in biased MD simulations. For the five-dimensional (5D) bottleneck, we perform an analysis of the latent CV space and identify the pair of CV coordinates that best separates the states of Hsp90. Interestingly, selecting a 2D CV out of the 5D CV space leads to better results than directly learning a 2D CV and allows observation of transitions between native states when running free energy biased dynamics.

Spatial arrangement of functional domains in OxyS stress response sRNA.

Small noncoding RNAs are an important class of regulatory RNAs in bacteria, often regulating responses to changes in environmental conditions. OxyS is a 110 nt, stable, trans-encoded small RNA found in Escherichia coli and is induced by an increased concentration of hydrogen peroxide. OxyS has an important regulatory role in cell stress response, affecting the expression of multiple genes. In this work, we investigated the structure of OxyS and the interaction with fhlA mRNA using nuclear magnetic resonance spectroscopy, small-angle X-ray scattering, and unbiased molecular dynamics simulations. We determined the secondary structures of isolated stem-loops and confirmed their structural integrity in OxyS. Unexpectedly, stem-loop SL4 was identified in the region that was predicted to be unstructured. Three-dimensional models of OxyS demonstrate that OxyS adopts an extended structure with four solvent-exposed stem-loops, which are available for interaction with other RNAs and proteins. Furthermore, we provide evidence of base-pairing between OxyS and fhlA mRNA.

Incorporation of N7-Platinated Guanines into Thermus Aquaticus (Taq) DNA Polymerase: Atomistic Insights from Molecular Dynamics Simulations.

In this work, we elucidated some key aspects of the mechanism of action of the cisplatin anticancer drug, cis-[Pt(NH3)2Cl2], involving direct interactions with free nucleotides. A comprehensive in silico molecular modeling analysis was conducted to compare the interactions of Thermus aquaticus (Taq) DNA polymerase with three distinct N7-platinated deoxyguanosine triphosphates: [Pt(dien)(N7-dGTP)] (1), cis-[Pt(NH3)2Cl(N7-dGTP)] (2), and cis-[Pt(NH3)2(H2O)(N7-dGTP)] (3) {dien = diethylenetriamine; dGTP = 5'-(2'-deoxy)-guanosine-triphosphate}, using canonical dGTP as a reference, in the presence of DNA. The goal was to elucidate the binding site interactions between Taq DNA polymerase and the tested nucleotide derivatives, providing valuable atomistic insights. Unbiased molecular dynamics simulations (200 ns for each complex) with explicit water molecules were performed on the four ternary complexes, yielding significant findings that contribute to a better understanding of experimental results. The molecular modeling highlighted the crucial role of a specific α-helix (O-helix) within the fingers subdomain, which facilitates the proper geometry for functional contacts between the incoming nucleotide and the DNA template needed for incorporation into the polymerase. The analysis revealed that complex 1 exhibits a much lower affinity for Taq DNA polymerase than complexes 2-3. The affinities of cisplatin metabolites 2-3 for Taq DNA polymerase were found to be quite similar to those of natural dGTP, resulting in a lower incorporation rate for complex 1 compared to complexes 2-3. These findings could have significant implications for the cisplatin mechanism of action, as the high intracellular availability of free nucleobases might promote the competitive incorporation of platinated nucleotides over direct cisplatin attachment to DNA. The study's insights into the incorporation of platinated nucleotides into the Taq DNA polymerase active site suggest that the role of platinated nucleotides in the cisplatin mechanism of action may have been previously underestimated.