Random Acceleration Molecular Dynamics Research Articles

Exhaustively Exploring the Prevalent Interaction Pathways of Ligands Targeting the Ligand-Binding Pocket of Farnesoid X Receptor via Combined Enhanced Sampling.

It is well-known that the potency of a drug is heavily associated with its kinetic and thermodynamic properties with the target. Nuclear receptors (NRs), as an important target family, play important roles in regulating a variety of physiological processes in vivo. However, it is hard to understand the drug-NR interaction process because of the closed structure of the ligand-binding domain (LBD) of the NR proteins, which apparently hinders the rational design of drugs with controllable kinetic properties. Therefore, understanding the underlying mechanism of the ligand-NR interaction process seems necessary to help NR drug design. However, it is usually difficult for experimental approaches to interpret the kinetic process of drug-target interactions. Therefore, in silico methods were utilized to explore the optimal binding/dissociation pathways of the NR ligands. Specifically, farnesoid X receptor (FXR) is considered here as the target system since it has been an important target for the treatment of bile acid metabolism-associated diseases, and a series of structures cocrystallized with diverse scaffold ligands were resolved. By using random acceleration molecular dynamics (RAMD) simulation and umbrella sampling (US), 5 main dissociation pathways (pathways I-V) were identified in 11 representative FXR ligands, with most of them (9/11) preferring to go through Pathway III and the remaining two favoring escaping from Pathway I and IV. Furthermore, key residues functioning in the three main dissociation pathways were revealed by the kinetic residue energy analysis (KREA) based on the US trajectories, which may serve as road-marker residues for rapid identification of the (un)binding pathways of FXR ligands. Moreover, the preferred pathways explored by RAMD simulations are in good agreement with the minimum free energy path identified by the US simulations with the Pearson R = 0.76 between the predicted binding affinity and the experimental data, suggesting that RAMD is suitable for applying in large-scale (un)binding-pathway exploration in the case of ligands with obscure binding tunnels to the target.

Binding Thermodynamics and Dissociation Kinetics Analysis Uncover the Key Structural Motifs of Phenoxyphenol Derivatives as the Direct InhA Inhibitors and the Hotspot Residues of InhA.

Given the current epidemic of multidrug-resistant tuberculosis, there is an urgent need to develop new drugs to combat drug-resistant tuberculosis. Direct inhibitors of the InhA target do not require activation and thus can overcome drug resistance caused by mutations in drug-activating enzymes. In this work, the binding thermodynamic and kinetic information of InhA to its direct inhibitors, phenoxyphenol derivatives, were explored through multiple computer-aided drug design (CADD) strategies. The results show that the van der Waals interactions were the main driving force for protein–ligand binding, among which hydrophobic residues such as Tyr158, Phe149, Met199 and Ile202 have high energy contribution. The AHRR pharmacophore model generated by multiple ligands demonstrated that phenoxyphenol derivatives inhibitors can form pi–pi stacking and hydrophobic interactions with InhA target. In addition, the order of residence time predicted by random acceleration molecular dynamics was consistent with the experimental values. The intermediate states of these inhibitors could form hydrogen bonds and van der Waals interactions with surrounding residues during dissociation. Overall, the binding and dissociation mechanisms at the atomic level obtained in this work can provide important theoretical guidance for the development of InhA direct inhibitors with higher activity and proper residence time.

Determination of Multidirectional Pathways for Ligand Release from the Receptor: A New Approach Based on Differential Evolution.

Steered molecular dynamics (SMD) simulation is a powerful method in computer-aided drug design as it can be used to access the relative binding affinity with high precision but with low computational cost. The success of SMD depends on the choice of the direction along which the ligand is pulled from the receptor-binding site. In most simulations, the unidirectional pathway was used, but in some cases, this choice resulted in the ligand colliding with the complex surface of the exit tunnel. To overcome this difficulty, several variants of SMD with multidirectional pulling have been proposed, but they are not completely devoid of disadvantages. Here, we have proposed to determine the direction of pulling with a simple scoring function that minimizes the receptor–ligand interaction, and an optimization algorithm called differential evolution is used for energy minimization. The effectiveness of our protocol was demonstrated by finding expulsion pathways of Huperzine A and camphor from the binding site of Torpedo California acetylcholinesterase and P450cam proteins, respectively, and comparing them with the previous results obtained using memetic sampling and random acceleration molecular dynamics. In addition, by applying this protocol to a set of ligands bound with LSD1 (lysine specific demethylase 1), we obtained a much higher correlation between the work of pulling force and experimental data on the inhibition constant IC50 compared to that obtained using the unidirectional approach based on minimal steric hindrance.

Protein-Ligand Dissociation Rate Constant from All-Atom Simulation.

Dissociation of a ligand isoniazid from a protein catalase was investigated using all-atom molecular dynamics (MD) simulations. Random acceleration MD (τ-RAMD) was used, in which a random artificial force applied to the ligand facilitates its dissociation. We have suggested a novel approach to extrapolate such obtained dissociation times to the zero-force limit assuming never before attempted universal exponential dependence of the bond strength on the applied force, allowing direct comparison with experimentally measured values. We have found that our calculated dissociation time was equal to 36.1 s with statistically significant values distributed in the interval of 0.2-72.0 s, which quantitatively matches the experimental value of 50 ± 8 s despite the extrapolation over 9 orders of magnitude in time.

Exploring the thermodynamic, kinetic and inhibitory mechanisms of 5-iTU targeting mitotic kinase haspin by integrated molecular dynamics.

As a human mitotic kinase, haspin is considered as a promising target for various diseases including cancers. However, no inhibitors targeting haspin have entered clinical trials presently. 5-iTU (5-iodotubercidin) is a useful and classical chemical probe for the investigation of haspin activity, but its inhibitory mechanism remains unclear. In this study, integrated molecular dynamics (MD) of conventional MD, extended adaptive biasing force (eABF), random acceleration MD and well-tempered metadynamics were applied to investigate the thermodynamic and kinetic features of 5-iTU and three derivatives targeting haspin. To emphasize the importance of gatekeeper Phe605, two haspin mutants (F605Y and F605T) were also built. The results showed that the binding affinity of 5-iTU and haspin was highest in all wild type (WT) systems, relying on the strong halogen aromatic π interaction between 5-iTU and gatekeeper Phe605. Gatekeeper mutations, because of damage to this interaction, led to the rearrangement of water distributions at the binding site and the decrease of 5-iTU residence times. Additionally, compared with the smaller 5-fTU, 5-iTU dissociated from WT haspin with more difficulty through distinct unbinding pathways. These findings will provide crucial guidance for the design and development of novel haspin inhibitors and the rational modification of existing inhibitors.

QM/MM study of the enzymatic catalysis

Enzyme catalysis generally includes multiple physical and chemical processes, such as the substrate transportion and binding to the active site, the chemical reaction in the protein confined environment, and the product release, where any chemical or nonchemical step is probably to dominate the activity of enzyme. In order to understand the enzymatic efficiency, the classical molecular dynamics (MM MD) and combined quantum and classical molecular dynamics (QM/MM MD) simulations, in combination with the umbrella sampling, have been used to explore mechanisms for the enzymatic catalysis and the substrate transportion in several biological systems, including the detoxification of the G-type nerve agent sarin by phosphotriesterase (PTE), the hydrolysis of uridine by the pyrimidine-specific nucleoside hydrolase Yeik (CU-NH), and the transportation of naphthalimide-polyamine compounds into the drug sites by the bovine serum albumin (BSA). Extensive QM/MM MD and MM MD simulations show that the wild-type PTE enzyme is capable of hydrolyzing sarin but with a low catalytic efficiency. Dissociation of the degraded product from the binuclear zinc center is predicted to be the rate-determining step with the free-energy barrier of 21.0 kcal/mol, and the multiple chemical steps are involved in the dissociation process. The P-F cleavage of the substrate sarin follows a two-step mechanism, in which the nucleophilic attack of the bridging hydroxide leads to the P-Oµ formation with the free-energy barrier of 9.8 kcal/mol, and the subsequent P-F cleavage and the proton transfer from the µ-OH to the residue Asp301 yields the degraded product with the free-energy span of 12.3 kcal/mol. The relatively strong hydrogen-bond interactions between the substrate uridine and key residues in the active site of CU-NH play an important role in the substrate specificity. The enzymatic N -glycosidic bond cleavage of uridine by CU-NH is the rate-limiting step with the free energy barrier of about 20 kcal/mol, and the substrate protonation less influences the activity of CU-NH, completely different from other nucleoside hydrolases. The combined random acceleration molecular dynamics and MD simulations (RAMD MD) have been used to explore possible transportation channels and the most favorable pathways for the delivery of the naphthalimide-polyamine complex to two drug sites of BSA, as well as their thermodynamic and dynamic properties. MM MD and RAMD MD simulations show that the selective specificity of these two drug sites strongly depends on the electron-withdrawing and electron-donating substituents of the substrate, which can be used for the design of new naphthalimide drugs. Such site-selectivity-dependence design strategy may open up an avenue in drug discovery. With the fast development of low-scaling QM methodologies and the application of artificial intelligence neural network approaches to theoretical and computational chemistry, it can be expected to reduce the computational costs of QM treatment and improve the efficiency of QM/MM, which makes the direct QM/MM study of larger and more complex systems become possible. In addition, the improvement and development of coarse-grained models can surmount the spatial and temporal limitation of multiscale calculations and simulations. Accordingly, global simulations of extremely large and complicated biosystems can be realized in the future, which may provide a theoretical basis for further expanding the application of enzyme engineering.

A workflow for exploring ligand dissociation from a macromolecule: Efficient random acceleration molecular dynamics simulation and interaction fingerprint analysis of ligand trajectories.

The dissociation of ligands from proteins and other biomacromolecules occurs over a wide range of timescales. For most pharmaceutically relevant inhibitors, these timescales are far beyond those that are accessible by conventional molecular dynamics (MD) simulation. Consequently, to explore ligand egress mechanisms and compute dissociation rates, it is necessary to enhance the sampling of ligand unbinding. Random Acceleration MD (RAMD) is a simple method to enhance ligand egress from a macromolecular binding site, which enables the exploration of ligand egress routes without prior knowledge of the reaction coordinates. Furthermore, the τRAMD procedure can be used to compute the relative residence times of ligands. When combined with a machine-learning analysis of protein-ligand interaction fingerprints (IFPs), molecular features that affect ligand unbinding kinetics can be identified. Here, we describe the implementation of RAMD in GROMACS 2020, which provides significantly improved computational performance, with scaling to large molecular systems. For the automated analysis of RAMD results, we developed MD-IFP, a set of tools for the generation of IFPs along unbinding trajectories and for their use in the exploration of ligand dynamics. We demonstrate that the analysis of ligand dissociation trajectories by mapping them onto the IFP space enables the characterization of ligand dissociation routes and metastable states. The combined implementation of RAMD and MD-IFP provides a computationally efficient and freely available workflow that can be applied to hundreds of compounds in a reasonable computational time and will facilitate the use of τRAMD in drug design.

Dynamics and Mechanism of Binding of Androstenedione to Membrane-Associated Aromatase.

Aromatase (CYP19A1) catalyzes the synthesis of estrogens from androgens and is an invaluable target of pharmacotherapy for estrogen-dependent cancers. CYP19A1 is also one of the most primordial human CYPs and, to the extent that its fundamental dynamics are conserved, is highly relevant to understanding those of the more recently evolved and promiscuous enzymes. A complementary approach employing molecular dynamics simulations and hydrogen-deuterium exchange mass spectrometry (HDX-MS) was employed to interrogate the changes in CYP19A1 dynamics coupled to binding androstenedione (ASD). Gaussian-accelerated molecular dynamics and HDX-MS agree that ASD globally suppresses CYP19A1 dynamics. Bimodal HDX patterns of the B'-C loop potentially arising from at least two conformations are present in free 19A1 only, supporting the possibility that conformational selection is operative. Random-acceleration molecular dynamics and adaptive biasing force simulations illuminate ASD's binding pathway, predicting ASD capture in the lipid headgroups and a pathway to the active site shielded from solvent. Intriguingly, the predicted access channel in 19A1 aligns well with the steroid binding sites of other human sterol-oxidizing CYPs.

Random acceleration and steered molecular dynamics simulations reveal the (un)binding tunnels in adenosine deaminase and critical residues in tunnels.

Adenosine deaminase (ADA) is an important enzyme related to purine nucleoside metabolism in human serum and various tissues. Abnormal ADA levels are related to a wide variety of diseases such as rheumatoid arthritis, AIDS, anemia, lymphoma, and leukemia and ADA is considered as a useful target for various diseases. Currently, ADA can be divided into open conformation and closed conformation according to the inhibitors of binding. As a consequence, we chose two inhibitors, namely, 6-hydroxy-1,6-dihydro purine nucleoside (PRH) and N-[4,5-bis(4-hydroxyphenyl)-1,3-thiazol-2-yl]hexanamide (FRK) to bind to ADA in the closed conformation or open conformation respectively. In this study, we performed the random acceleration molecular dynamics (RAMD) method, steered molecular dynamics (SMD) simulations and adaptive basing force (ABF) simulation to explore the unbinding tunnels and tunnel characteristics of the two inhibitors in ADA. Our results showed that PRH and FRK escaped from ADA using three main tunnels (namely, T1, T2, and T3). Inhibitors (PRH and FRK) escape through T3 more frequently and more easily. The results from ABF simulations confirm that the free energy barrier in T1 or T2 is larger than that in T3 when inhibitors dissociate from the ADA and have potential mean of force (PMF) depth. Moreover, in the complexes (ADA-PRH, ADA-FRK), we also found that the most active residue that remarkably contributed to the binding affinity is W117 in T3, and the residue played an important role in the unbinding tunnel for inhibitor leaving. Our theoretical study provided insight into the ADA inhibitor passway mechanism and may be a clue for potent ADA inhibitor design.

Unraveling the Unbinding Pathways of Products Formed in Catalytic Reactions Involved in SIRT1-3: A Random Acceleration Molecular Dynamics Simulation Study.

Sirtuins are a family of nicotinamide adenine dinucleotide (NAD+)-dependent enzymes, which undergo robust deacetylase activity, resulting in the production of nicotinamide. It is well known that nicotinamide, which is one of the products, can also act as an inhibitor for further deacetylation process by forming NAD+ again. Hence, the removal of nicotinamide from sirtuins is a demanding process, and the mechanistic understanding of the process remains elusive. In this investigation, we have made an attempt to unravel the unbinding pathways of nicotinamide from SIRT1, SIRT2, and SIRT3 (SIRT1-3) using Random Acceleration Molecular Dynamics (RAMD) Simulations, and we have successfully identified various unbinding channels. The selectivity of the egression channel is determined by using a thorough analysis of the frequency of egression trajectories. Similarly, various inhibitors have been docked with the active sites of SIRT1-3, and their egression pathways have been investigated to understand whether they follow the same egression pathway as that of nicotinamide. The residues that are responsible for the unbinding pathways have been determined from the analysis of RAMD trajectories. From these results, it is clear that phenylalanine and histidine residues play major roles in the egression of inhibitors. Additionally, the key residues Leu, Pro, Met, Phe, Tyr, and Ile are found to control the release by acting as gateway residues. The role of these residues from different egression channels has been studied by carrying out mutations with alanine residue. This is the first report on sirtuins, which demonstrates the novel unbinding pathways for nicotinamide/inhibitors. This work provides new insights for developing more promising SIRT1-3 inhibitors.

Machine Learning Analysis of τRAMD Trajectories to Decipher Molecular Determinants of Drug-Target Residence Times.

Drug-target residence times can impact drug efficacy and safety, and are therefore increasingly being considered during lead optimization. For this purpose, computational methods to predict residence times, τ, for drug-like compounds and to derive structure-kinetic relationships are desirable. A challenge for approaches based on molecular dynamics (MD) simulation is the fact that drug residence times are typically orders of magnitude longer than computationally feasible simulation times. Therefore, enhanced sampling methods are required. We recently reported one such approach: the τRAMD procedure for estimating relative residence times by performing a large number of random acceleration MD (RAMD) simulations in which ligand dissociation occurs in times of about a nanosecond due to the application of an additional randomly oriented force to the ligand. The length of the RAMD simulations is used to deduce τ. The RAMD simulations also provide information on ligand egress pathways and dissociation mechanisms. Here, we describe a machine learning approach to systematically analyze protein-ligand binding contacts in the RAMD trajectories in order to derive regression models for estimating τ and to decipher the molecular features leading to longer τ values. We demonstrate that the regression models built on the protein-ligand interaction fingerprints of the dissociation trajectories result in robust estimates of τ for a set of 94 drug-like inhibitors of heat shock protein 90 (HSP90), even for the compounds for which the length of the RAMD trajectories does not provide a good estimation of τ. Thus, we find that machine learning helps to overcome inaccuracies in the modeling of protein-ligand complexes due to incomplete sampling or force field deficiencies. Moreover, the approach facilitates the identification of features important for residence time. In particular, we observed that interactions of the ligand with the sidechain of F138, which is located on the border between the ATP binding pocket and a hydrophobic transient sub-pocket, play a key role in slowing compound dissociation. We expect that the combination of the τRAMD simulation procedure with machine learning analysis will be generally applicable as an aid to target-based lead optimization.

Uridine diphosphate release mechanism in O-N-acetylglucosamine (O-GlcNAc) transferase catalysis

O-linked N-acetylglucosamine transferase (OGT) is an essential enzyme that catalyzes the covalent bonding of N-acetylglucosamine (GlcNAc) to the hydroxyl group of a serine or threonine in the target protein. It plays an important role in many important cellular physiological catalytic reactions. Here, we determine the binding mode and the binding free energy of the OGT product (uridine diphosphate, UDP) as well as the hydrogen-bond-dependent release mechanism using extensive molecular dynamic simulations. The Lys634, Asn838, Gln839, Lys842, His901, and Asp925 residues were identified to play a major role in the UDP stabilization in the active site of OGT, where hydrogen bonding and π-π interactions mainly occur. The calculations on the mutant forms support our results. Sixteen possible release channels were identified while the two most favorable channels were determined using random acceleration molecular dynamics (RAMD) simulations combined with the constant velocity pulling (PCV) method. The thermodynamic and dynamic properties as along with the corresponding mechanism were determined and discussed according to the umbrella sampling technique. For the most optimal channel, the main free energy barrier is 13 kcal/mol, which probably originates from the hydrogen bonds between UDP and the Ala896 and Asp925 residues. Moreover, the unstable hydrogen bonds and the rollback of the ligand likely cause the other two small obstacles. This work clarifies the ligand transport mechanism in the OGT enzymatic process and is a great resource for designing inhibitors based on UDP or UDP-GlcNAc.

Product release mechanism and the complete enzyme catalysis cycle in yeast cytosine deaminase (yCD): A computational study

Yeast cytosine deaminase (yCD) is critical in gene-directed enzyme prodrug therapy as it catalyzes the hydrolytic deamination of cytosine. The product (uracil) release process is considered as rate-limiting in the whole enzymatic catalysis and includes the cleavage of the uracil-metal bond and the delivery of free uracil out of the reactive site. Herein extensive combined random acceleration molecular dynamics (RAMD) and molecular dynamics (MD) simulations coupled with the umbrella sampling technique have been performed to study the product transport mechanism. Five channels have been identified, and the thermodynamic and dynamic characterizations for the two most favorable channels have been determined and analyzed. The free energy barrier for the most beneficial pathway is about 13kcal/mol and mainly results from the cleavage of hydrogen bonds between the ligand uracil and surrounding residues Asn51, Glu64, and Asp155. The conjugated rings of Phe114 and Trp152 play gating and guiding roles in the product delivery via π⋯π van der Waals interactions with the product. Finally, the full cycle of the enzymatic catalysis has been determined, making the whole process computationally more precise.

Molecular basis of P450 OleTJE: an investigation of substrate binding mechanism and major pathways.

Cytochrome P450 OleTJE has attracted much attention for its ability to catalyze the decarboxylation of long chain fatty acids to generate alkenes, which are not only biofuel molecule, but also can be used broadly for making lubricants, polymers and detergents. In this study, the molecular basis of the binding mechanism of P450 OleTJE for arachidic acid, myristic acid, and caprylic acid was investigated by utilizing conventional molecular dynamics simulation and binding free energy calculations. Moreover, random acceleration molecular dynamics (RAMD) simulations were performed to uncover the most probable access/egress channels for different fatty acids. The predicted binding free energy shows an order of arachidic acid < myristic acid < caprylic acid. Key residues interacting with three substrates and residues specifically binding to one of them were identified. The RAMD results suggest the most likely channel for arachidic acid, myristic acid, and caprylic acid are 2e/2b, 2a and 2f/2a, respectively. It is suggested that the reaction is easier to carry out in myristic acid bound system than those in arachidic acid and caprylic acid bound system based on the distance of Hβ atom of substrate relative to P450 OleTJE Compound I states. This study provided novel insight to understand the substrate preference mechanism of P450 OleTJE and valuable information for rational enzyme design for short chain fatty acid decarboxylation.

Molecular Basis of GLUT4 in Glucose Transport: Atomistic Molecular Dynamics Study

The glucose transporter 4 (GLUT4) is one of the most important glucose transporter proteins for the absorption of glucose from the plasma circulation after a meal or during exercise. It is present in skeletal muscle, adipose tissue cells, cardiac muscle, and it has also been found in brain cells. It plays a significant role in the development of various diseases such as type 2 diabetes, cancer, and cardiac diseases. Inside a cell, GLUT4 is transported towards the cell membrane upon an insulin stimulus, leading to a 10- to 40-fold increase in the glucose uptake. In spite of its importance, the molecular mechanism of glucose transport by GLUT4 is still not clear. There is no crystal structure available for the GLUT4 protein either. However, using existing structural information of the other solved glucose transporter structures, we have modeled and validated the GLUT4 structure in three conformations: the outward-open, outward-occluded, and inward-open conformation. The GLUT4 models with glucose bound were subsequently embedded in a 1-palmitoyl-2-oleoyl-sn-glycero-3-phosphocholine (POPC) membrane and simulated over microsecond time scales using unbiased atomistic molecular dynamics simulations. In addition, we also carried out random acceleration molecular dynamics simulations to explore all possible pathways for glucose transport across the membrane. Our simulation studies revealed specific GLUT4 residues that captured the conformational changes in GLUT4 structure on glucose binding. Overall, the study provides atomistic level structural information on glucose transport and also provides one with ideas for the development of therapeutic agents blocking the function of GLUT4. This development work is important given that cancer cells express elevated levels of glucose transporter proteins and depend on increased glucose uptake for proliferation.

A Hidden Active Site in the Potential Drug Target Mycobacterium tuberculosis dUTPase Is Accessible through Small Amplitude Protein Conformational Changes

dUTPases catalyze the hydrolysis of dUTP into dUMP and pyrophosphate to maintain the proper nucleotide pool for DNA metabolism. Recent evidence suggests that dUTPases may also represent a selective drug target in mycobacteria because of the crucial role of these enzymes in maintaining DNA integrity. Nucleotide-hydrolyzing enzymes typically harbor a buried ligand-binding pocket at interdomain or intersubunit clefts, facilitating proper solvent shielding for the catalyzed reaction. The mechanism by which substrate binds this hidden pocket and product is released in dUTPases is unresolved because of conflicting crystallographic and spectroscopic data. We sought to resolve this conflict by using a combination of random acceleration molecular dynamics (RAMD) methodology and structural and biochemical methods to study the dUTPase from Mycobacterium tuberculosis In particular, the RAMD approach used in this study provided invaluable insights into the nucleotide dissociation process that reconciles all previous experimental observations. Specifically, our data suggest that nucleotide binding takes place as a small stretch of amino acids transiently slides away and partially uncovers the active site. The in silico data further revealed a new dUTPase conformation on the pathway to a relatively open active site. To probe this model, we developed the Trp21 reporter and collected crystallographic, spectroscopic, and kinetic data that confirmed the interaction of Trp21 with the active site shielding C-terminal arm, suggesting that the RAMD method is effective. In summary, our computational simulations and spectroscopic results support the idea that small loop movements in dUTPase allow the shuttlingof the nucleotides between the binding pocket and the solvent.

On Dioxygen and Substrate Access to Soluble Methane Monooxygenases: An all-Atom Molecular Dynamics Investigation in Water Solution.

In a preliminary exploration of the dummy model for diiron proteins, random-acceleration molecular dynamics (RAMD) revealed that a pure four-helix bundle structure, like hemerythrin, constitutes an efficient cage for dioxygen (O2 ), which can only leave from defined, albeit very broad, gates. However, this well ordered structure does not constitute an archetype on which to compare O2 permeation of other diiron proteins, like the complex of soluble methane monooxygenase hydroxylase with the regulatory protein (sMMOH-MMOB). The reason is that with this complex, unlike hemerythrin, the four helices of the four-helix bundle are heavily bent, and RAMD showed that most traps for O2 lie outside them. It was also observed that, in spite of a nearly identical van der Waals radius for O2 and the natural substrate CH4 , the latter behaves under RAMD as a bulkier molecule than O2 , requiring a higher external force to be brought out of sMMOH-MMOB along trajectories of viable length. All that determined with sMMOH-MMOB multiple gates and multiple pathways to each of them through several binding pockets, for both O2 and CH4 . Of the two equally preferred pathways for O2 , at right angle with one another, one proved to be in accordance with the Xe-atom mapping for sMMOH. In contrast, none of the pathways identified for CH4 proved to be in accordance with such mapping, CH4 looking for more open avenues instead.

Exploring ligand dissociation pathways from aminopeptidase N using random acceleration molecular dynamics simulation.

Aminopeptidase N (APN) is a zinc-dependent ectopeptidase involved in cell proliferation, secretion, invasion, and angiogenesis, and is widely recognized as an important cancer target. However, the mechanisms whereby ligands leave the active site of APN remain unknown. Investigating ligand dissociation processes is quite difficult, both in classical simulation methods and in experimental approaches. In this study, random acceleration molecular dynamics (RAMD) simulation was used to investigate the potential dissociation pathways of ligand from APN. The results revealed three pathways (channels A, B and C) for ligand release. Channel A, which matches the hypothetical channel region, was the most preferred region for bestatin to dissociate from the enzyme, and is probably the major channel for the inner bound ligand. In addition, two alternative channels (channels B and C) were shown to be possible pathways for ligand egression. Meanwhile, we identified key residues controlling the dynamic features of APN channels. Identification of the dissociation routes will provide further mechanistic insights into APN, which will benefit the development of more promising APN inhibitors. Graphical Abstract The release pathways of bestatin inside active site of aminopeptidase N were simulated using RAMD simulation.

Unveiling the Pathways of Dioxygen Through the C2 Component of the Environmentally Relevant Monooxygenase p-Hydroxyphenylacetate Hydroxylase from Acinetobacter baumannii: A Molecular Dynamics Investigation.

In this work, models of the homotetrameric C2 component of the monooxygenase p-hydroxyphenylacetate hydroxylase from Acinetobacter baumannii, in complex with dioxygen (O2 ) and, or not, the substrate p-hydroxyphenylacetate (HPA) were built. Both models proved to be amenable to random-acceleration molecular dynamics (RAMD) simulations, whereby a tiny randomly oriented external force, acting on O2 at the active site in front of flavin mononucleotide (FMNH(-) ), accelerated displacement of O2 toward the bulk solvent. This allowed us to carry out a sufficiently large number of RAMD simulations to be of statistical significance. The two systems behaved very similarly under RAMD, except for O2 leaving the active site more easily in the absence of HPA, but then finding similar obstacles in getting to the gate as when the active site was sheltered by HPA. This challenges previous conclusions that HPA can only reach the active center after that the C4aOOH derivative of FMNH(-) is formed, requiring uptake of O2 at the active site before HPA. According to these RAMD simulations, O2 could well get to FMNH(-) also in the presence of the substrate at the active site.

On the Permeation by Dioxygen of Urate Oxidase from Aspergillus flavus in Complex with Xanthine Anion: Dioxygen Pathways and a Portrait of the Enzyme Cavities from Molecular Dynamics Simulations in Water Solution.

This work describes molecular dynamics (MD) simulations in aqueous media for the complex of the homotetrameric urate oxidase (UOX) from Aspergillus flavus with xanthine anion (5) in the presence of dioxygen (O2 ). After 196.6 ns of trajectory from unrestrained MD, a O2 molecule was observed leaving the bulk solvent to penetrate the enzyme between two subunits, A/C. From here, the same O2 molecule was observed migrating, across subunit C, to the hydrophobic cavity that shares residue V227 with the active site. The latter was finally attained, after 378.3 ns of trajectory, with O2 at a bonding distance from 5. The reverse same O2 pathway, from 5 to the bulk solvent, was observed as preferred pathway under random acceleration MD (RAMD), where an external, randomly oriented force was acting on O2 . Both MD and RAMD simulations revealed several cavities populated by O2 during its migration from the bulk solvent to the active site or backwards. Paying attention to the last hydrophobic cavity that apparently serves as O2 reservoir for the active site, it was noticed that its volume undergoes ample fluctuations during the MD simulation, as expected from the thermal motion of a flexible protein, independently from the particular subunit and no matter whether the cavity is filled or not by O2 .