The dynamics of camphor in the cytochrome P450 CYP101D2

Studying the Collective Functional Response of a Receptor in Alchemical Ligand Binding Free Energy Simulations with Accelerated Solvation Layer Dynamics

Ligand binding free energy simulations (LB-FES) that involve sampling of protein functional conformations have been longstanding challenges in research on molecular recognition. Particularly, modeling of the conformational transition pathway and design of the heuristic biasing mechanism are severe bottlenecks for the existing enhanced configurational sampling (ECS) methods. Inspired by the key role of hydration in regulating conformational dynamics of macromolecules, this report proposes a novel ECS approach that facilitates binding-associated structural dynamics by accelerated hydration transitions in combination with the λ-exchange of free energy perturbation (FEP). Two challenging protein-ligand binding processes involving large configurational transitions of the receptor are studied, with hydration transitions at binding sites accelerated by Hamiltonian-simulated annealing of the hydration layer. Without the need for pathway analysis or ad hoc barrier flattening potential, LB-FES were performed with FEP/λ-exchange molecular dynamics simulation at a minor overhead for annealing of the hydration layer. The LB-FES studies showed that the accelerated rehydration significantly enhances the collective conformational transitions of the receptor, and convergence of binding affinity calculations is obtained at a sweet-spot simulation time scale. Alchemical LB-FES with the proposed ECS strategy is free from the effort of trial and error for the setup and realizes efficient on-the-fly sampling for the collective functional response of the receptor and bound water and therefore presents a practical approach to high-throughput screening in drug discovery.

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.

Identification of (-)-bornyl diphosphate synthase from Blumea balsamifera and its application for (-)-borneol biosynthesis in Saccharomyces cerevisiae

Borneol is a precious monoterpenoid with two chiral structures, (-)-borneol and (+)-borneol. Bornyl diphosphate synthase is the key enzyme in the borneol biosynthesis pathway. Many (+)-bornyl diphosphate synthases have been reported, but no (-)-bornyl diphosphate synthases have been identified. Blumea balsamifera leaves are rich in borneol, almost all of which is (-)-borneol. In this study, we identified a high-efficiency (-)-bornyl diphosphate synthase (BbTPS3) from B. balsamifera that converts geranyl diphosphate (GPP) to (-)-bornyl diphosphate, which is then converted to (-)-borneol after dephosphorylation in vitro. BbTPS3 exhibited a K_m value of 4.93 ± 1.38 μM for GPP, and the corresponding k_cat value was 1.49 s⁻¹. Multiple strategies were applied to obtain a high-yielding (-)-borneol producing yeast strain. A codon-optimized BbTPS3 protein was introduced into the GPP high-yield strain MD, and the resulting MD-B1 strain produced 1.24 mg·L^-1 (-)-borneol. After truncating the N-terminus of BbTPS3 and adding a Kozak sequence, the (-)-borneol yield was further improved by 4-fold to 4.87 mg·L^-1. Moreover, the (-)-borneol yield was improved by expressing the fusion protein module of ERG20^F96W-N127W-YRSQI-t14-BbTPS3K2, resulting in a final yield of 12.68 mg·L^-1 in shake flasks and 148.59 mg·L^-1 in a 5-L bioreactor. This work is the first reported attempt to produce (-)-borneol by microbial fermentation.

Spontaneous Ligand Access Events to Membrane-Bound Cytochrome P450 2D6 Sampled at Atomic Resolution

The membrane-anchored enzyme Cytochrome P450 2D6 (CYP2D6) is involved in the metabolism of around 25% of marketed drugs and its metabolic performance shows a high interindividual variation. While it was suggested that ligands access the buried active site of the enzyme from the membrane, no proof from unbiased simulations has been provided to support this hypothesis. Laboratory experiments fail to capture the access process which is suspected to influence binding kinetics. Here, we applied unbiased molecular dynamics (MD) simulations to investigate the access of ligands to wild-type CYP2D6, as well as the allelic variant CYP2D6*53. In multiple simulations, substrates accessed the active site of the enzyme from the protein-membrane interface to ultimately adopt a conformation that would allow a metabolic reaction. We propose the necessary steps for ligand access and the results suggest that the increased metabolic activity of CYP2D6*53 might be caused by a facilitated ligand uptake.

The Oxidation of Hydrophobic Aromatic Substrates by Using a Variant of the P450 Monooxygenase CYP101B1

The cytochrome P450 monooxygenase CYP101B1, from a Novosphingobium bacterium is able to bind and oxidise aromatic substrates but at a lower activity and efficiency than norisoprenoids and monoterpenoid esters. Histidine 85 of CYP101B1 aligns with tyrosine 96 of CYP101A1, which, in the latter enzyme forms the only hydrophilic interaction with its substrate, camphor. The histidine residue of CYP101B1 was mutated to phenylalanine with the aim of improving the activity of the enzyme for hydrophobic substrates. The H85F mutant lowered the binding affinity and activity of the enzyme for β-ionone and altered the oxidation selectivity. This variant also showed enhanced affinity and activity towards alkylbenzenes, styrenes and methylnaphthalenes. For example the rate of product formation for acenaphthene oxidation was improved sixfold to 245 nmol per nmol CYP per min. Certain disubstituted naphthalenes and substrates, such as phenylcyclohexane and biphenyls, were oxidised with lower activity by the H85F variant. Variants at H85 (A and G) designed to introduce additional space into the active site so as to accommodate these larger substrates did not improve the oxidation activity. As the H85F mutant of CYP101B1 improved the oxidation of hydrophobic substrates, this residue is likely to be in the substrate binding pocket or the access channel of the enzyme. The side chain of the histidine might interact with the carbonyl groups of the favoured norisoprenoid substrates of CYP101B1.

Thermodynamics of camphor migration in cytochrome P450cam by atomistic simulations

Understanding the mechanisms of ligand binding to enzymes is of paramount importance for the design of new drugs. Here, we report on the use of a novel biased molecular dynamics (MD) methodology to study the mechanism of camphor binding to cytochrome P450cam. Microsecond-long MD simulations allowed us to observe reaction coordinates characterizing ligand diffusion from the active site of cytochrome P450cam to solvent via three egress routes. These atomistic simulations were used to estimate thermodynamic quantities along the reaction coordinates and indicate diverse binding configurations. The results suggest that the diffusion of camphor along the pathway near the substrate recognition site (SRS) is thermodynamically preferred. In addition, we show that the diffusion near the SRS is triggered by a transition from a heterogeneous collection of closed ligand-bound conformers to the basin comprising the open conformations of cytochrome P450cam. The conformational change accompanying this switch is characterized by the retraction of the F and G helices and the disorder of the B' helix. These results are corroborated by experimental studies and provide detailed insight into ligand binding and conformational behavior of the cytochrome family. The presented methodology is general and can be applied to other ligand-protein systems.

Memetic algorithms for ligand expulsion from protein cavities

Ligand diffusion through a protein interior is a fundamental process governing biological signaling and enzymatic catalysis. A complex topology of channels in proteins leads often to difficulties in modeling ligand escape pathways by classical molecular dynamics simulations. In this paper, two novel memetic methods for searching the exit paths and cavity space exploration are proposed: Memory Enhanced Random Acceleration (MERA) Molecular Dynamics (MD) and Immune Algorithm (IA). In MERA, a pheromone concept is introduced to optimize an expulsion force. In IA, hybrid learning protocols are exploited to predict ligand exit paths. They are tested on three protein channels with increasing complexity: M2 muscarinic G-protein-coupled receptor, enzyme nitrile hydratase, and heme-protein cytochrome P450cam. In these cases, the memetic methods outperform simulated annealing and random acceleration molecular dynamics. The proposed algorithms are general and appropriate in all problems where an accelerated transport of an object through a network of channels is studied.

Access Path to the Ligand Binding Pocket May Play a Role in Xenobiotics Selection by AhR

Understanding of multidrug binding at the atomic level would facilitate drug design and strategies to modulate drug metabolism, including drug transport, oxidation, and conjugation. Therefore we explored the mechanism of promiscuous binding of small molecules by studying the ligand binding domain, the PAS-B domain of the aryl hydrocarbon receptor (AhR). Because of the low sequence identities of PAS domains to be used for homology modeling, structural features of the widely employed HIF-2α and a more recent suitable template, CLOCK were compared. These structures were used to build AhR PAS-B homology models. We performed molecular dynamics simulations to characterize dynamic properties of the PAS-B domain and the generated conformational ensembles were employed in in silico docking. In order to understand structural and ligand binding features we compared the stability and dynamics of the promiscuous AhR PAS-B to other PAS domains exhibiting specific interactions or no ligand binding function. Our exhaustive in silico binding studies, in which we dock a wide spectrum of ligand molecules to the conformational ensembles, suggest that ligand specificity and selection may be determined not only by the PAS-B domain itself, but also by other parts of AhR and its protein interacting partners. We propose that ligand binding pocket and access channels leading to the pocket play equally important roles in discrimination of endogenous molecules and xenobiotics.

The efficient and selective biocatalytic oxidation of norisoprenoid and aromatic substrates by CYP101B1 from Novosphingobium aromaticivorans DSM12444

CYP101B1 fromNovosphingobium aromaticivoransoxidises ionone derivatives and phenylcyclohexane with high activity and regioselectivity.

Insights into the influence of 5-HT2c aminoacidic variants with the inhibitory action of serotonin inverse agonists and antagonists

Specific modulation of serotonin 5-HT(2C) G protein-coupled receptors may be therapeutic for obesity and neuropsychiatric disorders. The different efficacy of drugs targeting these receptors are due to the presence of genetic variants in population and this variability is still hard to predict. Therefore, in order to administer the more suitable drug, taking into account patient genotype, it is necessary to know the molecular effects of its gene nucleotide variations. In this work, starting from an accurate 3D model of 5-HT(2C), we focus on the prediction of the possible effect of some single nucleotide polymorphisms (SNPs) producing amino acidic changes in proximity of the 5-HT(2C) ligand binding site. Particularly we chose a set of 5-HT(2C) inverse agonists and antagonists which have high inhibitory activity. After prediction of the structures of the receptor-ligand complexes using molecular docking tools, we performed full atom molecular dynamics simulations in explicit lipid bilayer monitoring the interactions between ligands and trans-membrane helices of the receptor, trying to infer relations with their biological activity. Serotonin, as the natural ligand was chosen as reference compound to advance a hypothesis able to explain the receptor inhibition mechanism. Indeed we observed a different behavior between the antagonists and inverse agonist with respect to serotonin or unbounded receptor, which could be responsible, even if not directly, of receptor's inactivation. Furthermore, we analyzed five aminoacidic variants of 5HT(2C) receptor observing alterations in the interactions between ligands and receptor which give rise to changes of free energy values for every complex considered.