A multiscale approach to modelling drug metabolism by membrane-bound cytochrome P450 enzymes

Equilibrium landscape of ingress/egress channels and gating residues of the Cytochrome P450 3A4

The Cytochrome P450 (CYP) enzymes metabolize a variety of drugs, which may potentially lead to toxicity or reduced efficacy when drugs are co-administered. These drug-drug interactions are often manifested by CYP3A4, the most prevalent of all CYP isozymes. We carried out multiple MD simulations employing CAVER to quantify the channels, and Hidden Markov Models (HMM) to characterize the behavior of the gating residues. We discuss channel properties, bottleneck residues with respect to their likelihood to deem the respective channel ingress or egress, gating residues regarding their open or closed states, and channel location relative to the membrane. Channels do not display coordinated motion and randomly transition between different conformations. Gateway residues also behave in a random fashion. Our findings shed light on the equilibrium behavior of the gating residues and channels in the apo state.

Key regulators in the architecture of substrate access/egress channels in mammalian cytochromes P450 governing flexibility in substrate oxyfunctionalization

Cytochrome P450s (CYP) represent a superfamily of b-type hemoproteins catalyzing oxifunctionalization of a vast array of endogenous and exogenous compounds. The present review focuses on assessment of the topology of prospective determinants in substrate entry and product release channels of mammalian P450s, steering the conformational dynamics of substrate accessibility and productive ligand orientation toward the iron-oxene core. Based on a generalized, CYP3A4-related construct, the sum of critical elements from diverse target enzymes was found to cluster within the known substrate recognition sites. The majority of prevalent substrate access/egress tunnels revealed to be of fairly balanced functional importance. The hydrophobicity profile of the candidates revealed to be the most salient feature in functional interaction throughout the conduits, while bulkiness of the residues imposes steric restrictions on substrate traveling. Thus, small amino acids such as prolines and glycines serve as hinges, driving conformational flexibility in ligand passage. Similarly, bottlenecks in the tunnel architecture, being narrowest encounter points within the CYP3A4 model, have a vital function in substrate selectivity along with clusters of aromatic amino acids acting as gatekeepers. In addition, peripheral patches in conduits may house determinants modulating allosteric cooperativity between remote and central domains in the P450 structure. Remarkably, the bulk critical residues lining tunnels in the various isozymes reside in helices B'/C and F/G inclusive of their interhelical turns as well as in helix I. This suggests these regions to represent hotspots for targeted genetic engineering to tailor more sophisticated mammalian P450s exploitable in industrial, biotechnological and medicinal areas.

Reliably assessing the electronic structure of cytochrome P450 on today's classical computers and tomorrow's quantum computers

Chemical simulation is one of the most promising applications for future quantum computers. It is thought that quantum computers may enable accurate simulation for complex molecules that are otherwise impossible to simulate classically; that is, it displays quantum advantage. To better understand quantum advantage in chemical simulation, we explore what quantum and classical resources are required to simulate a series of pharmaceutically relevant molecules. Using classical methods, we show that reliable classical simulation of these molecules requires significant resources and therefore is a promising candidate for quantum simulation. We estimate the quantum resources, both in overall simulation time and the size. The insights from this study pave the way for future quantum simulation of complex molecules.

An accurate assessment of how quantum computers can be used for chemical simulation, especially their potential computational advantages, provides important context on how to deploy these future devices. To perform this assessment reliably, quantum resource estimates must be coupled with classical computations attempting to answer relevant chemical questions and to define the classical algorithms simulation frontier. Herein, we explore the quantum computation and classical computation resources required to assess the electronic structure of cytochrome P450 enzymes (CYPs) and thus define a classical–quantum advantage boundary. This is accomplished by analyzing the convergence of density matrix renormalization group plus n-electron valence state perturbation theory (DMRG+NEVPT2) and coupled-cluster singles doubles with noniterative triples [CCSD(T)] calculations for spin gaps in models of the CYP catalytic cycle that indicate multireference character. The quantum resources required to perform phase estimation using qubitized quantum walks are calculated for the same systems. Compilation into the surface code provides runtime estimates to compare directly to DMRG runtimes and to evaluate potential quantum advantage. Both classical and quantum resource estimates suggest that simulation of CYP models at scales large enough to balance dynamic and multiconfigurational electron correlation has the potential to be a quantum advantage problem and emphasizes the important interplay between classical computations and quantum algorithms development for chemical simulation.

Refining details of the structural and electronic properties of the CuB site in pMMO enzyme through sequential molecular dynamics/CPKS-EPR calculations

This work investigated the structural and electronic properties of the copper mononuclear site of the PmoB part of the pMMO enzyme at the molecular level. We propose that the Cu_B catalytic site in the soluble portion of pMMO at room temperature and under physiological conditions is a mononuclear copper complex in a distorted octahedral arrangement with the residues His³³, His¹³⁷, and His¹³⁹ on the equatorial base and two water molecules on the axial axis. Our view was based on the molecular dynamics results and DFT calculations of the electronic paramagnetic resonance parameters and comparisons with experimental EPR data. This new proposed model for the Cu_B site brings additional support concerning the recent experimental evidence, which pointed out that a saturated coordination sphere of the copper ion in the Cu_B center is an essential factor that makes it less efficient than the Cu_C site in the methane oxidation. Therefore, according to the Cu_B site model proposed here, an additional step involving a displacement of at least one water molecule of the copper coordination sphere by the O₂ molecule prior to its activation must be necessary. This scenario is less likely to occur in the Cu_C center once this one is buried in the alpha-helices, which are part of the pMMO structure bound to the membrane wall, and consequently located in a less solvent-exposed region. In addition, we also present a simple and efficient sequential S-MD/CPKS protocol to compute EPR parameters that can, in principle, be expanded for the study of other copper-containing proteins.

Machine learning-driven identification of drugs inhibiting cytochrome P450 2C9

Cytochrome P450 2C9 (CYP2C9) is a major drug-metabolizing enzyme that represents 20% of the hepatic CYPs and is responsible for the metabolism of 15% of drugs. A general concern in drug discovery is to avoid the inhibition of CYP leading to toxic drug accumulation and adverse drug-drug interactions. However, the prediction of CYP inhibition remains challenging due to its complexity. We developed an original machine learning approach for the prediction of drug-like molecules inhibiting CYP2C9. We created new predictive models by integrating CYP2C9 protein structure and dynamics knowledge, an original selection of physicochemical properties of CYP2C9 inhibitors, and machine learning modeling. We tested the machine learning models on publicly available data and demonstrated that our models successfully predicted CYP2C9 inhibitors with an accuracy, sensitivity and specificity of approximately 80%. We experimentally validated the developed approach and provided the first identification of the drugs vatalanib, piriqualone, ticagrelor and cloperidone as strong inhibitors of CYP2C9 with IC values <18 μM and sertindole, asapiprant, duvelisib and dasatinib as moderate inhibitors with IC50 values between 40 and 85 μM. Vatalanib was identified as the strongest inhibitor with an IC50 value of 0.067 μM. Metabolism assays allowed the characterization of specific metabolites of abemaciclib, cloperidone, vatalanib and tarafenacin produced by CYP2C9. The obtained results demonstrate that such a strategy could improve the prediction of drug-drug interactions in clinical practice and could be utilized to prioritize drug candidates in drug discovery pipelines.

Mechanistic Understanding from Molecular Dynamics in Pharmaceutical Research 2: Lipid Membrane in Drug Design

We review the use of molecular dynamics (MD) simulation as a drug design tool in the context of the role that the lipid membrane can play in drug action, i.e., the interaction between candidate drug molecules and lipid membranes. In the standard "lock and key" paradigm, only the interaction between the drug and a specific active site of a specific protein is considered; the environment in which the drug acts is, from a biophysical perspective, far more complex than this. The possible mechanisms though which a drug can be designed to tinker with physiological processes are significantly broader than merely fitting to a single active site of a single protein. In this paper, we focus on the role of the lipid membrane, arguably the most important element outside the proteins themselves, as a case study. We discuss work that has been carried out, using MD simulation, concerning the transfection of drugs through membranes that act as biological barriers in the path of the drugs, the behavior of drug molecules within membranes, how their collective behavior can affect the structure and properties of the membrane and, finally, the role lipid membranes, to which the vast majority of drug target proteins are associated, can play in mediating the interaction between drug and target protein. This review paper is the second in a two-part series covering MD simulation as a tool in pharmaceutical research; both are designed as pedagogical review papers aimed at both pharmaceutical scientists interested in exploring how the tool of MD simulation can be applied to their research and computational scientists interested in exploring the possibility of a pharmaceutical context for their research.

From System Modeling to System Analysis: The Impact of Resolution Level and Resolution Distribution in the Computer-Aided Investigation of Biomolecules

The ever increasing computer power, together with the improved accuracy of atomistic force fields, enables researchers to investigate biological systems at the molecular level with remarkable detail. However, the relevant length and time scales of many processes of interest are still hardly within reach even for state-of-the-art hardware, thus leaving important questions often unanswered. The computer-aided investigation of many biological physics problems thus largely benefits from the usage of coarse-grained models, that is, simplified representations of a molecule at a level of resolution that is lower than atomistic. A plethora of coarse-grained models have been developed, which differ most notably in their granularity; this latter aspect determines one of the crucial open issues in the field, i.e. the identification of an optimal degree of coarsening, which enables the greatest simplification at the expenses of the smallest information loss. In this review, we present the problem of coarse-grained modeling in biophysics from the viewpoint of system representation and information content. In particular, we discuss two distinct yet complementary aspects of protein modeling: on the one hand, the relationship between the resolution of a model and its capacity of accurately reproducing the properties of interest; on the other hand, the possibility of employing a lower resolution description of a detailed model to extract simple, useful, and intelligible information from the latter.

Molecular Dynamics Simulations in Drug Discovery and Pharmaceutical Development

Molecular dynamics (MD) simulations have become increasingly useful in the modern drug development process. In this review, we give a broad overview of the current application possibilities of MD in drug discovery and pharmaceutical development. Starting from the target validation step of the drug development process, we give several examples of how MD studies can give important insights into the dynamics and function of identified drug targets such as sirtuins, RAS proteins, or intrinsically disordered proteins. The role of MD in antibody design is also reviewed. In the lead discovery and lead optimization phases, MD facilitates the evaluation of the binding energetics and kinetics of the ligand-receptor interactions, therefore guiding the choice of the best candidate molecules for further development. The importance of considering the biological lipid bilayer environment in the MD simulations of membrane proteins is also discussed, using G-protein coupled receptors and ion channels as well as the drug-metabolizing cytochrome P450 enzymes as relevant examples. Lastly, we discuss the emerging role of MD simulations in facilitating the pharmaceutical formulation development of drugs and candidate drugs. Specifically, we look at how MD can be used in studying the crystalline and amorphous solids, the stability of amorphous drug or drug-polymer formulations, and drug solubility. Moreover, since nanoparticle drug formulations are of great interest in the field of drug delivery research, different applications of nano-particle simulations are also briefly summarized using multiple recent studies as examples. In the future, the role of MD simulations in facilitating the drug development process is likely to grow substantially with the increasing computer power and advancements in the development of force fields and enhanced MD methodologies.

CYP2J2 Molecular Recognition: A New Axis for Therapeutic Design

Cytochrome P450 (CYP) epoxygenases are a special subset of heme-containing CYP enzymes capable of performing the epoxidation of polyunsaturated fatty acids (PUFA) and the metabolism of xenobiotics. This dual functionality positions epoxygenases along a metabolic crossroad. Therefore, structure-function studies are critical for understanding their role in bioactive oxy-lipid synthesis, drug-PUFA interactions, and for designing therapeutics that directly target the epoxygenases. To better exploit CYP epoxygenases as therapeutic targets, there is a need for improved understanding of epoxygenase structure-function. Of the characterized epoxygenases, human CYP2J2 stands out as a potential target because of its role in cardiovascular physiology. In this review, the early research on the discovery and activity of epoxygenases is contextualized to more recent advances in CYP epoxygenase enzymology with respect to PUFA and drug metabolism. Additionally, this review employs CYP2J2 epoxygenase as a model system to highlight both the seminal works and recent advances in epoxygenase enzymology. Herein we cover CYP2J2's interactions with PUFAs and xenobiotics, its tissue-specific physiological roles in diseased states, and its structural features that enable epoxygenase function. Additionally, the enumeration of research on CYP2J2 identifies the future needs for the molecular characterization of CYP2J2 to enable a new axis of therapeutic design.

The Effect of Force-Field Parameters on Cytochrome P450-Membrane Interactions: Structure and Dynamics

The simulation of membrane proteins requires compatible protein and lipid force fields that reproduce the properties of both the protein and the lipid bilayer. Cytochrome P450 enzymes are bitopic membrane proteins with a transmembrane helical anchor and a large cytosolic globular domain that dips into the membrane. As such, they are representative and challenging examples of membrane proteins for simulations, displaying features of both peripheral and integral membrane proteins. We performed molecular dynamics simulations of three cytochrome P450 isoforms (2C9, 2C19 and 1A1) in a 2-oleoyl-1-palmitoyl-sn-glycerol-3-phosphocholine bilayer using two AMBER force field combinations: GAFF-LIPID with ff99SB for the protein, and LIPID14 with ff14SB for the protein. Comparison of the structural and dynamic properties of the proteins, the lipids and the protein-membrane interactions shows differing sensitivity of the cytochrome P450 isoforms to the choice of force field, with generally better agreement with experiment for the LIPID14 + ff14SB combination.

Lipophilic Metabolic Efficiency (LipMetE) and Drug Efficiency Indices to Explore the Metabolic Properties of the Substrates of Selected Cytochrome P450 Isoforms

Cytochrome P450 (CYP450) enzymes belong to a superfamily of heme-containing proteins that are involved in the metabolism of structurally diverse endogenous and exogenous compounds. Various proof-of-concept studies indicate that metabolic stability and intrinsic clearance of CYP450 substrates are linked with the respective lipophilicity (log P or log D). This necessitates the normalization of lipophilicity (log P or log D) of a given CYP450 substrate with respect to its metabolic stability (LipMetE) and intrinsic clearance (log₁₀CL_int,u). Therefore, in this article, the LipMetE values of already known substrates of CYP1A2, CYP2C9, CYP2C19, CYP2D6, and CYP3A4, including some marketed drugs, have been calculated to elucidate the relationship between lipophilicity (log D _7.4) and in vitro clearance. Moreover, various drug efficiency metrics including lipophilic efficiency (LipE) and ligand efficiency (LE) have been evaluated, and the thresholds of these parameters have been defined for the CYP450 substrates exhibiting normalized LipMetE. Our results indicate that for a given range of LipMetE, greater the log D value of the substrate the more avidly it binds to a given CYP450 enzyme and shows more intrinsic clearance (log₁₀CL_int,u). Overall, the majority of the model substrates of CYP450 isoforms and already marketed drugs in our datasets exhibit log D _7.4 values of ∼2.5 with LipMetE values in the range of 0-2.5 and LipE values of ≤3. Overall, consideration of these parameters in ADME profiling could aid in reducing the drug failure rate in the later stages of clinical investigations.

User-Friendly Quantum Mechanics: Applications for Drug Discovery

Quantum mechanics (QM) methods provide a fine description of receptor-ligand interactions and of chemical reactions. Their use in drug design and drug discovery is increasing, especially for complex systems including metal ions in the binding sites, for the design of highly selective inhibitors, for the optimization of bi-specific compounds, to understand enzymatic reactions, and for the study of covalent ligands and prodrugs. They are also used for generating molecular descriptors for predictive QSAR/QSPR models and for the parameterization of force fields. Thanks to the continuous increase of computational power offered by GPUs and to the development of sophisticated algorithms, QM methods are becoming part of the standard tools used in computer-aided drug design (CADD). We present the most used QM methods and software packages, and we discuss recent representative applications in drug design and drug discovery.

Molecular Dynamics Simulation Framework to Probe the Binding Hypothesis of CYP3A4 Inhibitors

The Cytochrome P450 family of heme-containing proteins plays a major role in catalyzing phase I metabolic reactions, and the CYP3A4 subtype is responsible for the metabolism of many currently marketed drugs. Additionally, CYP3A4 has an inherent affinity for a broad spectrum of structurally diverse chemical entities, often leading to drug-drug interactions mediated by the inhibition or induction of the metabolic enzyme. The current study explores the binding of selected highly efficient CYP3A4 inhibitors by docking and molecular dynamics (MD) simulation protocols and their binding free energy calculated using the WaterSwap method. The results indicate the importance of binding pocket residues including Phe57, Arg105, Arg106, Ser119, Arg212, Phe213, Thr309, Ser312, Ala370, Arg372, Glu374, Gly481 and Leu483 for interaction with CYP3A4 inhibitors. The residue-wise decomposition of the binding free energy from the WaterSwap method revealed the importance of binding site residues Arg106 and Arg372 in the stabilization of all the selected CYP3A4-inhibitor complexes. The WaterSwap binding energies were further complemented with the MM(GB/PB)SA results and it was observed that the binding energies calculated by both methods do not differ significantly. Overall, our results could guide towards the use of multiple computational approaches to achieve a better understanding of CYP3A4 inhibition, subsequently leading to the design of highly specific and efficient new chemical entities with suitable ADMETox properties and reduced side effects.

Prediction of Ligand Transport along Hydrophobic Enzyme Nanochannels

Buried active sites of enzymes are connected to the bulk solvent through a network of hydrophobic channels. We developed a discretized model that can accurately predict ligand transport along hydrophobic channels up to six orders of magnitude faster than any other existing method. The non-dimensional nature of the model makes it applicable to any hydrophobic channel/ligand combination.

Multiscale Simulations of Biological Membranes: The Challenge To Understand Biological Phenomena in a Living Substance

Biological membranes are tricky to investigate. They are complex in terms of molecular composition and structure, functional over a wide range of time scales, and characterized by nonequilibrium conditions. Because of all of these features, simulations are a great technique to study biomembrane behavior. A significant part of the functional processes in biological membranes takes place at the molecular level; thus computer simulations are the method of choice to explore how their properties emerge from specific molecular features and how the interplay among the numerous molecules gives rise to function over spatial and time scales larger than the molecular ones. In this review, we focus on this broad theme. We discuss the current state-of-the-art of biomembrane simulations that, until now, have largely focused on a rather narrow picture of the complexity of the membranes. Given this, we also discuss the challenges that we should unravel in the foreseeable future. Numerous features such as the actin-cytoskeleton network, the glycocalyx network, and nonequilibrium transport under ATP-driven conditions have so far received very little attention; however, the potential of simulations to solve them would be exceptionally high. A major milestone for this research would be that one day we could say that computer simulations genuinely research biological membranes, not just lipid bilayers.

Characterization of Lipid-Protein Interactions and Lipid-Mediated Modulation of Membrane Protein Function through Molecular Simulation

The cellular membrane constitutes one of the most fundamental compartments of a living cell, where key processes such as selective transport of material and exchange of information between the cell and its environment are mediated by proteins that are closely associated with the membrane. The heterogeneity of lipid composition of biological membranes and the effect of lipid molecules on the structure, dynamics, and function of membrane proteins are now widely recognized. Characterization of these functionally important lipid-protein interactions with experimental techniques is however still prohibitively challenging. Molecular dynamics (MD) simulations offer a powerful complementary approach with sufficient temporal and spatial resolutions to gain atomic-level structural information and energetics on lipid-protein interactions. In this review, we aim to provide a broad survey of MD simulations focusing on exploring lipid-protein interactions and characterizing lipid-modulated protein structure and dynamics that have been successful in providing novel insight into the mechanism of membrane protein function.

Multiscale Methods in Drug Design Bridge Chemical and Biological Complexity in the Search for Cures

Drug action is inherently multiscale: it connects molecular interactions to emergent properties at cellular and larger scales. Simulation techniques at each of these different scales are already central to drug design and development, but methods capable of connecting across these scales will extend understanding of complex mechanisms and the ability to predict biological effects. Improved algorithms, ever-more-powerful computing architectures and the accelerating growth of rich datasets are driving advances in multiscale modeling methods capable of bridging chemical and biological complexity from the atom to the cell. Particularly exciting is the development of highly detailed, structure-based, physical simulations of biochemical systems, which are now able to access experimentally relevant timescales for large systems and, at the same time, achieve unprecedented accuracy. In this Perspective, we discuss how emerging data-rich, physics-based multiscale approaches are of the cusp of realizing long-promised impact in the discovery, design and development of novel therapeutics. We highlight emerging methods and applications in this growing field, and outline how different scales can be combined in practical modelling and simulation strategies.

Lipid molecules can induce an opening of membrane-facing tunnels in cytochrome P450 1A2

Cytochrome P450 1A2 (P450 1A2, CYP1A2) is a membrane-bound enzyme that oxidizes a broad range of hydrophobic substrates. The structure and dynamics of both the catalytic and trans-membrane (TM) domains of this enzyme in the membrane/water environment were investigated using a multiscale computational approach, including coarse-grained and all-atom molecular dynamics. Starting from the spontaneous self-assembly of the system containing the TM or soluble domain immersed in randomized dilauroyl phosphatidylcholine (DLPC)/water mixture into their respective membrane-bound forms, we reconstituted the membrane-bound structure of the full-length P450 1A2. This structure includes a TM helix that spans the membrane, while being connected to the catalytic domain by a short flexible loop. Furthermore, in this model, the upper part of the TM helix interacts directly with a conserved and highly hydrophobic N-terminal proline-rich segment of the catalytic domain; this segment and the FG loop are immersed in the membrane, whereas the remaining portion of the catalytic domain remains exposed to aqueous solution. The shallow membrane immersion of the catalytic domain induces a depression in the opposite intact layer of the phospholipids. This structural effect may help in stabilizing the position of the TM helix directly beneath the catalytic domain. The partial immersion of the catalytic domain also allows for the enzyme substrates to enter the active site from either aqueous solution or phospholipid environment via several solvent- and membrane-facing tunnels in the full-length P450 1A2. The calculated tunnel dynamics indicated that the opening probability of the membrane-facing tunnels is significantly enhanced when a DLPC molecule spontaneously penetrates into the membrane-facing tunnel 2d. The energetics of the lipid penetration process were assessed by the linear interaction energy (LIE) approximation, and found to be thermodynamically feasible.

Membrane-embedded substrate recognition by cytochrome P450 3A4

Cytochrome P450 3A4 (CYP3A4) is the dominant xenobiotic-metabolizing enzyme in the liver and intestine and is involved in the disposition of more than 50% of drugs. Because of its ability to bind multiple substrates, its reaction kinetics are complex, and its association with the microsomal membrane confounds our understanding of how this enzyme recognizes and recruits diverse substrates. Testosterone (TST) hydroxylation is the prototypical CYP3A4 reaction, displaying positive homotropic cooperativity with three binding sites. Here, exploiting the capability of accelerated molecular dynamics (aMD) to sample events in the millisecond regime, I performed >25-μs aMD simulations in the presence of three TST molecules. These simulations identified high-occupancy surface-binding sites as well as a pathway for TST ingress into the CYP3A4 active site originating in the membrane. Adaptive biasing force analysis of the latter pathway revealed a metastable intermediate that could constitute a third binding site at high TST concentrations. Prompted by the observation that interactions between TST and the G'-helix mobilize the ligand into the active site, a free-energy analysis of TST distribution in the membrane was conducted and revealed that the depth of the G'-helix is optimal for extracting TST. In summary, these simulations confirm separate, but adjacent substrate-binding sites within the enzyme and the existence of an auxiliary TST-binding site. The broader impact of these simulations is that they support a mechanism in which cytochromes P450 directly recruit membrane-solubilized substrates.

Systems biology of cellular membranes: a convergence with biophysics

Systems biology and systems medicine have played an important role in the last two decades in shaping our understanding of biological processes. While systems biology is synonymous with network maps and '-omics' approaches, it is not often associated with mechanical processes. Here, we make the case for considering the mechanical and geometrical aspects of biological membranes as a key step in pushing the frontiers of systems biology of cellular membranes forward. We begin by introducing the basic components of cellular membranes, and highlight their dynamical aspects. We then survey the functions of the plasma membrane and the endomembrane system in signaling, and discuss the role and origin of membrane curvature in these diverse cellular processes. We further give an overview of the experimental and modeling approaches to study membrane phenomena. We close with a perspective on the converging futures of systems biology and membrane biophysics, invoking the need to include physical variables such as location and geometry in the study of cellular membranes. WIREs Syst Biol Med 2017, 9:e1386. doi: 10.1002/wsbm.1386 For further resources related to this article, please visit the WIREs website.

Progress in Molecular Dynamics Simulations of Gram-Negative Bacterial Cell Envelopes

Bacteria are protected by complex molecular architectures known as the cell envelope. The cell envelope is composed of regions with distinct chemical compositions and physical properties, namely, membranes and a cell wall. To develop novel antibiotics to combat pathogenic bacteria, molecular level knowledge of the structure, dynamics, and interplay between the chemical components of the cell envelope that surrounds bacterial cells is imperative. In addition, conserved molecular patterns associated with the bacterial envelope are recognized by receptors as part of the mammalian defensive response to infection, and an improved understanding of bacteria-host interactions would facilitate the search for novel immunotherapeutics. This Perspective introduces an emerging area of computational biology: multiscale molecular dynamics simulations of chemically complex models of bacterial lipids and membranes. We discuss progress to date, and identify areas for future development that will enable the study of aspects of the membrane components that are as yet unexplored by computational methods.

Molecular dynamics investigations of membrane-bound CYP2C19 polymorphisms reveal distinct mechanisms for peripheral variants by long-range effects on the enzymatic activity

The results reveal distinct mechanisms for enzymatic activity deficiencies upon two peripheral variants in CYP2C19.

Atomistic modelling of scattering data in the Collaborative Computational Project for Small Angle Scattering (CCP-SAS)

The capabilities of current computer simulations provide a unique opportunity to model small-angle scattering (SAS) data at the atomistic level, and to include other structural constraints ranging from molecular and atomistic energetics to crystallography, electron microscopy and NMR. This extends the capabilities of solution scattering and provides deeper insights into the physics and chemistry of the systems studied. Realizing this potential, however, requires integrating the experimental data with a new generation of modelling software. To achieve this, the CCP-SAS collaboration (http://www.ccpsas.org/) is developing open-source, high-throughput and user-friendly software for the atomistic and coarse-grained molecular modelling of scattering data. Robust state-of-the-art molecular simulation engines and molecular dynamics and Monte Carlo force fields provide constraints to the solution structure inferred from the small-angle scattering data, which incorporates the known physical chemistry of the system. The implementation of this software suite involves a tiered approach in which GenApp provides the deployment infrastructure for running applications on both standard and high-performance computing hardware, and SASSIE provides a workflow framework into which modules can be plugged to prepare structures, carry out simulations, calculate theoretical scattering data and compare results with experimental data. GenApp produces the accessible web-based front end termed SASSIE-web, and GenApp and SASSIE also make community SAS codes available. Applications are illustrated by case studies: (i) inter-domain flexibility in two- to six-domain proteins as exemplified by HIV-1 Gag, MASP and ubiquitin; (ii) the hinge conformation in human IgG2 and IgA1 antibodies; (iii) the complex formed between a hexameric protein Hfq and mRNA; and (iv) synthetic 'bottlebrush' polymers.

Multi-class and multi-scale models of complex biological phenomena

Computational modeling has significantly impacted our ability to analyze vast (and exponentially increasing) quantities of experimental data for a variety of applications, such as drug discovery and disease forecasting. Single-scale, single-class models persist as the most common group of models, but biological complexity often demands more sophisticated approaches. This review surveys modeling approaches that are multi-class (incorporating multiple model types) and/or multi-scale (accounting for multiple spatial or temporal scales) and describes how these models, and combinations thereof, should be used within the context of the problem statement. We end by highlighting agent-based models as an intuitive, modular, and flexible framework within which multi-scale and multi-class models can be implemented.

A hybrid molecular dynamics/fluctuating hydrodynamics method for modelling liquids at multiple scales in space and time

A new 3D implementation of a hybrid model based on the analogy with two-phase hydrodynamics has been developed for the simulation of liquids at microscale. The idea of the method is to smoothly combine the atomistic description in the molecular dynamics zone with the Landau-Lifshitz fluctuating hydrodynamics representation in the rest of the system in the framework of macroscopic conservation laws through the use of a single "zoom-in" user-defined function s that has the meaning of a partial concentration in the two-phase analogy model. In comparison with our previous works, the implementation has been extended to full 3D simulations for a range of atomistic models in GROMACS from argon to water in equilibrium conditions with a constant or a spatially variable function s. Preliminary results of simulating the diffusion of a small peptide in water are also reported.

Incorporation of charged residues in the CYP2J2 F-G loop disrupts CYP2J2-lipid bilayer interactions

CYP2J2 epoxygenase is an extrahepatic, membrane bound cytochrome P450 (CYP) that is primarily found in the heart and mediates endogenous fatty acid metabolism. CYP2J2 interacts with membranes through an N-terminal anchor and various non-contiguous hydrophobic residues. The molecular details of the motifs that mediate membrane interactions are complex and not fully understood. To gain better insights of these complex protein-lipid interactions, we employed molecular dynamics (MD) simulations using a highly mobile membrane mimetic (HMMM) model that enabled multiple independent spontaneous membrane binding events to be captured. Simulations revealed that CYP2J2 engages with the membrane at the F-G loop through hydrophobic residues Trp-235, Ille-236, and Phe-239. To explore the role of these residues, three F-G loop mutants were modeled from the truncated CYP2J2 construct (Δ34) which included Δ34-I236D, Δ34-F239H and Δ34-I236D/F239H. Using the HMMM coordinates of CYP2J2, the simulations were extended to a full POPC membrane which showed a significant decrease in the depth of insertion for each of the F-G loop mutants. The CYP2J2 F-G loop mutants were expressed in E. coli and were shown to be localized to the cytosolic fraction at a greater percentage relative to construct Δ34. Notably, the functional data demonstrated that the double mutant, Δ34-I236D/F239H, maintained native-like enzymatic activity. The membrane insertion characteristics were examined by monitoring CYP2J2 Trp-quenching fluorescence spectroscopy upon binding nanodiscs containing pyrene phospholipids. Relative to the Δ34 construct, the F-G loop mutants exhibited lower Trp quenching and membrane insertion. Taken together, the results suggest that the mutants exhibit a different membrane topology in agreement with the MD simulations and provide important evidence towards the involvement of key residues in the F-G loop of CYP2J2.

In pursuit of an accurate spatial and temporal model of biomolecules at the atomistic level: a perspective on computer simulation

Despite huge advances in the computational techniques available for simulating biomolecules at the quantum-mechanical, atomistic and coarse-grained levels, there is still a widespread perception amongst the experimental community that these calculations are highly specialist and are not generally applicable by researchers outside the theoretical community. In this article, the successes and limitations of biomolecular simulation and the further developments that are likely in the near future are discussed. A brief overview is also provided of the experimental biophysical methods that are commonly used to probe biomolecular structure and dynamics, and the accuracy of the information that can be obtained from each is compared with that from modelling. It is concluded that progress towards an accurate spatial and temporal model of biomacromolecules requires a combination of all of these biophysical techniques, both experimental and computational.

Flexible docking-based molecular dynamics/steered molecular dynamics calculations of protein-protein contacts in a complex of cytochrome P450 1A2 with cytochrome b5

Formation of transient complexes of cytochrome P450 (P450) with another protein of the endoplasmic reticulum membrane, cytochrome b5 (cyt b5), dictates the catalytic activities of several P450s. Therefore, we examined formation and binding modes of the complex of human P450 1A2 with cyt b5. Docking of soluble domains of these proteins was performed using an information-driven flexible docking approach implemented in HADDOCK. Stabilities of the five unique binding modes of the P450 1A2-cyt b5 complex yielded by HADDOCK were evaluated using explicit 10 ns molecular dynamics (MD) simulations in aqueous solution. Further, steered MD was used to compare the stability of the individual P450 1A2-cyt b5 binding modes. The best binding mode was characterized by a T-shaped mutual orientation of the porphyrin rings and a 10.7 Å distance between the two redox centers, thus satisfying the condition for a fast electron transfer. Mutagenesis studies and chemical cross-linking, which, in the absence of crystal structures, were previously used to deduce specific P450-cyt b5 interactions, indicated that the negatively charged convex surface of cyt b5 binds to the positively charged concave surface of P450. Our simulations further elaborate structural details of this interface, including nine ion pairs between R95, R100, R138, R362, K442, K455, and K465 side chains of P450 1A2 and E42, E43, E49, D65, D71, and heme propionates of cyt b5. The universal heme-centric system of internal coordinates was proposed to facilitate consistent classification of the orientation of the two porphyrins in any protein complex.