Investigation of indazole unbinding pathways in CYP2E1 by molecular dynamics simulations

Mechanism of Regio- and Enantioselective Hydroxylation of Arachidonic Acid Catalyzed by Human CYP2E1: A Combined Molecular Dynamics and Quantum Mechanics/Molecular Mechanics Study

Regio- and enantioselective hydroxylation of free fatty acids by human cytochrome P450 2E1 (CYP2E1) plays an important role in metabolic regulation and has significant pathological implications. Despite extensive research, the detailed hydroxylation mechanism of CYP2E1 remains incompletely understood. To clarify the origins of regioselectivity and enantioselectivity observed for CYP2E1-mediated fatty acid hydroxylation, molecular dynamics (MD) simulations and quantum mechanics/molecular mechanics (QM/MM) calculations were performed. MD simulations provided key insights into the proximity of arachidonic acid's carbon atoms to the reactive iron(IV)-oxo moiety in compound I (Cpd I), with the ω-1 position being closest, indicating higher reactivity at this site. QM/MM calculations identified hydrogen abstraction as the rate-determining step, with the ω-1S transition state exhibiting the lowest energy barrier, consistent with experimentally observed enantioselectivity. Energy decomposition analysis revealed that variations in quantum mechanical energy (ΔEQM) significantly influence reaction barriers, with the most efficient hydrogen abstraction occurring at the ω-1S and ω-2R positions. These findings underscore the importance of substrate positioning within the active site in determining product selectivity. Comparisons with two related P450s, P450BM3 and P450SPα, further highlighted the critical role of active site architecture and substrate positioning in modulating selectivity. While surrounding residues do not directly dictate product selectivity, they shape the active site environment and influence substrate positioning. Furthermore, our analysis revealed a previously unrecognized catalytic role of Ala299. These findings provide a deeper mechanistic understanding of human CYP2E1 and offer valuable insights for its precise engineering in targeted C-H functionalization.

Molecular Basis of the Recognition of Cholesterol by Cytochrome P450 46A1 along the Major Access Tunnel

CYP46A1 is an important potential target for the treatment of Alzheimer's disease (AD), which is the most common neurodegenerative disease among older individuals. However, the binding mechanism between CYP46A1 and substrate cholesterol (CH) has not been clarified and will not be conducive to the research of relevant drug molecules. In this study, we integrated molecular docking, molecular dynamics (MD) simulations, and adaptive steered MD simulations to explore the recognition and binding mechanism of CYP46A1 with CH. Two key factors affecting the interaction between CH and CYP46A1 are determined: one is a hydrophobic cavity formed by seven hydrophobic residues (F80, Y109, L112, I222, W368, F371, and T475), which provides nonpolar interactions to stabilize CH, and the other is a hydrogen bond formed by H81 and CH, which ensures the binding direction of CH. In addition, the tunnel analysis results show that tunnel 2a is identified as the primary pathway of CH. The entry of CH induces tunnel 2e to close and tunnel w to open. Our results may provide effective clues for the design of drugs based on the substrate for AD and improve our understanding of the structure-function of CYP46A1.

Application of in vitro PAMPA technique and in silico computational methods for blood-brain barrier permeability prediction of novel CNS drug candidates

Permeability assessment of small molecules through the blood-brain barrier (BBB) plays a significant role in the development of effective central nervous system (CNS) drug candidates. Since in vivo methods for BBB permeability estimation require a lot of time and resources, in silico and in vitro approaches are becoming increasingly popular nowadays for faster and more economical predictions in early phases of drug discovery. In this work, through application of in vitro parallel artificial membrane permeability assay (PAMPA-BBB) and in silico computational methods we aimed to examine the passive permeability of eighteen compounds, which affect serotonin and dopamine levels in the CNS. The data set was consisted of novel six human dopamine transporter (hDAT) substrates that were previously identified as the most promising lead compounds for further optimisation to achieve neuroprotective effect, twelve approved CNS drugs, and their related compounds. Firstly, PAMPA methods was used to experimentally determine effective BBB permeability (P_e) for all studied compounds and obtained results were further submitted for quantitative structure permeability relationship (QSPR) analysis. QSPR models were built by using three different statistical methods: stepwise multiple linear regression (MLR), partial least square (PLS), and support-vector machine (SVM), while their predictive capability was tested through internal and external validation. Obtained statistical parameters (MLR- R²_pred=-0.10; PLS- R²_pred=0.64, r²_m=0.69, r^/2_m=0.44; SVM- R²_pred=0.57, r²_m=0.72, r^/2_m=0.55) indicated that the SVM model is superior over others. The most important molecular descriptors (H₀p and SolvEMt_3D) were identified and used to propose structural modifications of the examined compounds in order to improve their BBB permeability. Moreover, steered molecular dynamics (SMD) simulation was employed to comprehensively investigate the permeability pathway of compounds through a lipid bilayer. Taken together, the created QSPR model could be used as a reliable and fast pre-screening tool for BBB permeability prediction of structurally related CNS compounds, while performed MD simulations provide a good foundation for future in silico examination.

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.

Tryptophan-75 Is a Low-Energy Channel-Gating Residue that Facilitates Substrate Egress/Access in Cytochrome P450 2D6

CYP2D6 is a major drug metabolizing enzyme with a buried active site. Channels leading to the active site from various enzyme surfaces are believed to facilitate ligand egress and access to the active site. The present study used molecular dynamics (MD) and in vitro studies with CYP2D6*1 and a Trp75-to-Ala mutant to examine channel gating in CYP2D6 by Trp75. MD simulations measured energy landscapes of Trp75 conformations and simulated substrate passage within channel 2b using bufuralol as a model substrate. Trp75 alternated between multiple stable states that supported substrate transport along channel 2b with low-energy barriers between states (∼ -1 kcal/mol). Trp75 conformations were stabilized primarily by hydrogen bonding between Trp75 and Glu222, Asn226, Ala225, or Gln72. Energy barriers were low between Trp75 conformations, allowing Trp75 to easily move between various conformations over time and to function in both binding to and moving substrates in the 2b channel of CYP2D6. Michaelis-Menten kinetic studies completed with purified enzyme in a reconstituted system showed overall reduced enzyme efficiency for metabolism of bufuralol and dextromethorphan by the Trp75Ala mutant compared with CYP2D6*1. In stopped-flow measurements, k off for dextromethorphan was decreased in the absence of Trp75. Our results support a role for Trp75 in substrate shuttling to the active site of CYP2D6. SIGNIFICANCE STATEMENT: Using combined molecular dynamics and in vitro assays, this study shows for the first time a role for Trp75 as a channel entrance gating residue in the mechanism of substrate binding/unbinding in CYP2D6. Energy landscapes derived from molecular dynamics were used to quantitate the strength of gating, and kinetics assays showed the impact on enzyme efficiency and k off of a Trp75Ala mutation.

Prediction of Drug-Drug Interactions Related to Inhibition or Induction of Drug-Metabolizing Enzymes

Drug-drug interaction (DDI) is the phenomenon of alteration of the pharmacological activity of a drug(s) when another drug(s) is co-administered in cases of so-called polypharmacy. There are three types of DDIs: pharmacokinetic (PK), pharmacodynamic, and pharmaceutical. PK is the most frequent type of DDI, which often appears as a result of the inhibition or induction of drug-metabolising enzymes (DME). In this review, we summarise in silico methods that may be applied for the prediction of the inhibition or induction of DMEs and describe appropriate computational methods for DDI prediction, showing the current situation and perspectives of these approaches in medicinal and pharmaceutical chemistry. We review sources of information on DDI, which can be used in pharmaceutical investigations and medicinal practice and/or for the creation of computational models. The problem of the inaccuracy and redundancy of these data are discussed. We provide information on the state-of-the-art physiologically- based pharmacokinetic modelling (PBPK) approaches and DME-based in silico methods. In the section on ligand-based methods, we describe pharmacophore models, molecular field analysis, quantitative structure-activity relationships (QSAR), and similarity analysis applied to the prediction of DDI related to the inhibition or induction of DME. In conclusion, we discuss the problems of DDI severity assessment, mention factors that influence severity, and highlight the issues, perspectives and practical using of in silico methods.

Four Major Channels Detected in the Cytochrome P450 3A4: A Step toward Understanding Its Multispecificity

We computed the network of channels of the 3A4 isoform of the cytochrome P450 (CYP) on the basis of 16 crystal structures extracted from the Protein Data Bank (PDB). The calculations were performed with version 2 of the CCCPP software that we developed for this research project. We identified the minimal cost paths (MCPs) output by CCCPP as probable ways to access to the buried active site. The algorithm of calculation of the MCPs is presented in this paper, with its original method of visualization of the channels. We found that these MCPs constitute four major channels in CYP3A4. Among the many channels proposed by Cojocaru et al. in 2007, we found that only four of them open in 3A4. We provide a refined description of these channels together with associated quantitative data.

Molecular dynamics investigations of regioselectivity of anionic/aromatic substrates by a family of enzymes: a case study of diclofenac binding in CYP2C isoforms

The CYP2C subfamily is of particular importance in the metabolism of drugs, food toxins, and procarcinogens. Like other P450 subfamilies, 2C enzymes share a high sequence identity, but significantly contribute in different ways to hepatic capacity to metabolize drugs. They often metabolize the same substrate to more than one product with different catalytic sites. Because it is challenging to characterize experimentally, much still remains unknown about the reason for why the substrate regioselectivity of these closely related subfamily members is different. Here, we have investigated the structural features of CYP2C8, CYP2C9, and CYP2C19 bound with their shared substrate diclofenac to elucidate the underlying molecular mechanism for the substrate regioselectivity of CYP2C subfamily enzymes. The obtained results demonstrate how a sequence divergence for the active site residues causes heterogeneous variations in the secondary structures and in major tunnel selections, and further affects the shape and chemical properties of the substrate-binding site. Structural analysis and free energy calculations showed that the most important determinants of regioselectivity among the CYP2C isoforms are the geometrical features of the active sites, as well as the hydrogen bonds and the hydrophobic interactions, mainly presenting as the various locations of Arg108 and substitutions of Phe205 for Ile205 in CYP2C8. The MM-GB/SA calculations combined with PMF results accord well with the experimental KM values, bridging the gap between the theory and the experimentally observed results of binding affinity differences. The present study provides important insights into the structure-function relationships of CYP2C subfamily enzymes, the knowledge of ligand binding characteristics and key residue contributions could guide future experimental and computational work on the synthesis of drugs with better pharmacokinetic properties so that CYP interactions could be avoided.

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

Cytochrome P450 OleT_JE 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 OleT_JE 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 OleT_JE Compound I states. This study provided novel insight to understand the substrate preference mechanism of P450 OleT_JE and valuable information for rational enzyme design for short chain fatty acid decarboxylation.

Structural-functional adaptations of porcine CYP1A1 to metabolize polychlorinated dibenzo-p-dioxins

Polychlorinated dibenzo-p-dioxins (PCDDs) are widespread by-products of human industrial activity. They accumulate in tissues of animals and humans, exerting numerous adverse effects on different systems. In living organisms, dioxins are metabolized by enzymes of the cytochrome P450 family, including CYP1A1. Particular dioxin congeners differ in their toxicity level and ability to undergo biodegradation. Since the molecular mechanisms underlying dioxin susceptibility or resistance to biodegradation are unknown, in the present study the molecular interactions between five selected dioxins and porcine CYP1A1 protein were investigated. It was found that the ability of a dioxin to undergo CYP1A1-mediated degradation is associated mainly with the number and position of chlorine atoms in the dioxin molecule. Among all examined congeners, 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD) demonstrated the highest affinity to CYP1A1 and, at the same time, the greatest distance to the active site of the enzyme. Interestingly, in contrast to other dioxins, the binding of the TCDD molecule to the porcine CYP1A1 active site resulted in a rapid and continuous closure of substrate channels. All the information may help to explain the extended half-life of TCDD in living organisms as well as its high toxicity.

Molecular Dynamics and Free Energy Simulations of Phenylacetate and CO2 Release from AMDase and Its G74C/C188S Mutant: A Possible Rationale for the Reduced Activity of the Latter

Arylmalonate decarboxylase (AMDase) catalyzes the decarboxylation of α-aryl-α-methyl malonates to produce optically pure α-arylpropionates of industrial and medicinal importance. Herein, atomistic molecular dynamics simulations have been carried out to delineate the mechanism of the release of product molecules phenylacetate (PAC) and carbon dioxide (CO₂), from the wild-type (WT) and its G74C/C188S mutant enzymes. Both of the product molecules follow a crystallographically characterized solvent-accessible channel to come out of the protein interior. A higher free energy barrier for the release of PAC from G74C/C188S compared to that in the WT is consistent with the experimentally observed compromised efficiency of the mutant. The release of CO₂ precedes that of PAC; free energy barriers for CO₂ and PAC release in the WT enzyme are calculated to be ∼1-2 and ∼23 kcal/mol, respectively. Postdecarboxylation, CO₂ moves toward a hydrophobic pocket formed by Pro 14, Leu 38, Leu 40, Leu 77, and the side chain of Tyr 48 which serves as its temporary "reservoir". CO₂ releases following a channel mainly decorated by apolar residues, unlike in the case of oxalate decarboxylase where polar residues mediate its transport.

Screening of hepatitis C NS5B polymerase inhibitors containing benzothiadiazine core: a steered molecular dynamics

Hepatic C virus (HCV) is a global health problem, resulting in liver cirrhosis and inflammation that can develop to hepatocellular carcinoma and fatality. The NS5B polymerase of HCV plays an important role in viral RNA replication process, making it an attractive therapeutic target for design and development of anti-HCV drugs. To search new potent compounds against the HCV NS5B polymerase, the molecular docking and the steered molecular dynamics (SMD) simulation techniques were performed. The potential potent inhibitors of the NS5B polymerase were screened out from the ZINC database using structural similarity search and molecular docking technique. Five top-hit compounds (the ZINC compounds 49888724, 49054741, 49777239, 49793673, and 49780355) were then studied by the SMD simulations based on the hypothesis that a high rupture force relates to a high binding efficiency. The results demonstrated that the ZINC compound 49888724 had a greater maximum rupture force, reflecting a good binding strength and inhibitory potency than known inhibitors and the rest four ZINC compounds. Therefore, our finding indicated that the ZINC compound 49888724 is a potential candidate to be a novel NS5B inhibitor for further design. Besides, the van der Waals interaction could be considered as the main contribution for stabilizing the NS5B-ligand complex.

The molecular mechanism of ligand unbinding from the human telomeric G-quadruplex by steered molecular dynamics and umbrella sampling simulations

G-quadruplexes are attractive drug targets in cancer therapy. Understanding the mechanisms of the binding-unbinding processes involving biomolecules and molecular recognition is essential for designing new drugs of G-quadruplexes. We performed steered molecular dynamics and umbrella sampling simulations to investigate the molecular mechanism and kinetics of ligand unbinding processes of the basket, propeller and hybrid G-quadruplex structures. Our studies of the ligand charge effect showed that Coulomb interaction plays a significant role in stabilizing the G-quadruplex structure in the unbinding process. The free energy profiles were carried out and the free energy changes associated with the unbinding process were computed quantitatively, whereas these results could help to identify accessible binding sites and transient interactions. The dynamics of the hydration shell water molecules around the G-quadruplex exhibits an abnormal Brownian motion, and the thickness and free energy of the hydration shell were estimated. A two-step relaxation scheme was theoretically developed to describe the kinetic reaction of BMVC and G-quadruplex interactions. Our computed results fall in a reasonable range of experimental data. The present investigation could be helpful in the structure-based drug design.

Ligand tunnels in T. brucei and human CYP51: Insights for parasite-specific drug design

BACKGROUND

Cytochrome P450 sterol 14α-demethylase (CYP51) is an essential enzyme for sterol biosynthesis and a target for anti-parasitic drug design. However, the design of parasite-specific drugs that inhibit parasitic CYP51 without severe side effects remains challenging. The active site of CYP51 is situated in the interior of the protein. Here, we characterize the potential ligand egress routes and mechanisms in Trypanosoma brucei and human CYP51 enzymes.

METHODS

We performed Random Acceleration Molecular Dynamics simulations of the egress of four different ligands from the active site of models of soluble and membrane-bound T. brucei CYP51 and of soluble human CYP51.

RESULTS

In the simulations, tunnel 2f, which leads to the membrane, was found to be the predominant ligand egress tunnel for all the ligands studied. Tunnels S, 1 and W, which lead to the cytosol, were also used in T. brucei CYP51, whereas tunnel 1 was the only other tunnel used significantly in human CYP51. The common tunnels found previously in other CYPs were barely used. The ligand egress times were shorter for human than T. brucei CYP51, suggesting lower barriers to ligand passage. Two gating residues, F105 and M460, in T. brucei CYP51 that modulate the opening of tunnels 2f and S were identified.

CONCLUSIONS

Although the main egress tunnel was the same, differences in the tunnel-lining residues, ligand passage and tunnel usage were found between T. brucei and human CYP51s.

GENERAL SIGNIFICANCE

The results provide a basis for the design of selective anti-parasitic agents targeting the ligand tunnels.

In silico methods for predicting drug-drug interactions with cytochrome P-450s, transporters and beyond

Drug-drug interactions (DDIs) are associated with severe adverse effects that may lead to the patient requiring alternative therapeutics and could ultimately lead to drug withdrawal from the market if they are severe. To prevent the occurrence of DDI in the clinic, experimental systems to evaluate drug interaction have been integrated into the various stages of the drug discovery and development process. A large body of knowledge about DDI has also accumulated through these studies and pharmacovigillence systems. Much of this work to date has focused on the drug metabolizing enzymes such as cytochrome P-450s as well as drug transporters, ion channels and occasionally other proteins. This combined knowledge provides a foundation for a hypothesis-driven in silico approach, using either cheminformatics or physiologically based pharmacokinetics (PK) modeling methods to assess DDI potential. Here we review recent advances in these approaches with emphasis on hypothesis-driven mechanistic models for important protein targets involved in PK-based DDI. Recent efforts with other informatics approaches to detect DDI are highlighted. Besides DDI, we also briefly introduce drug interactions with other substances, such as Traditional Chinese Medicines to illustrate how in silico modeling can be useful in this domain. We also summarize valuable data sources and web-based tools that are available for DDI prediction. We finally explore the challenges we see faced by in silico approaches for predicting DDI and propose future directions to make these computational models more reliable, accurate, and publically accessible.

Computational insights into inhibitory mechanism of azole compounds against human aromatase

We investigated the inhibitory mechanism of azole aromatase inhibitors. The results showed that letrozole and imazalil prefer different unbinding pathways.

Structural basis for cooperative binding of azoles to CYP2E1 as interpreted through guided molecular dynamics simulations

CYP2E1 metabolizes a wide array of small, hydrophobic molecules, resulting in their detoxification or activation into carcinogens through Michaelis-Menten as well as cooperative mechanisms. Nevertheless, the molecular determinants for CYP2E1 specificity and metabolic efficiency toward these compounds are still unknown. Herein, we employed computational docking studies coupled to molecular dynamics simulations to provide a critical perspective for understanding a structural basis for cooperativity observed for an array of azoles from our previous binding and catalytic studies (Hartman et al., 2014). The resulting 28 CYP2E1 complexes in this study revealed a common passageway for azoles that included a hydrophobic steric barrier causing a pause in movement toward the active site. The entrance to the active site acted like a second sieve to restrict access to the inner chamber. Collectively, these interactions impacted the final orientation of azoles reaching the active site and hence could explain differences in their biochemical properties observed in our previous studies, such as the consequences of methylation at position 5 of the azole ring. The association of a second azole demonstrated significant differences in interactions stabilizing the bound complex than observed for the first binding event. Intermolecular interactions occurred between the two azoles as well as CYP2E1 residue side chains and backbone and involved both hydrophobic contacts and hydrogen bonds. The relative importance of these interactions depended on the structure of the respective azoles indicating the absence of specific defining criteria for binding unlike the well-characterized dominant role of hydrophobicity in active site binding. Consequently, the structure activity relationships described here and elsewhere are necessary to more accurately identify factors impacting the observation and significance of cooperativity in CYP2E1 binding and catalysis toward drugs, dietary compounds, and pollutants.

Unbinding pathways of VEGFR2 inhibitors revealed by steered molecular dynamics

A detailed atomistic description of the unbinding process of sorafenib and sunitinib, two known VEGFR2 inhibitors clinically used to treat renal cell carcinoma, was unraveled by using steered molecular dynamics (SMD) simulations. While sunitinib is a fast-dissociating binder, sorafenib exhibits quite a long residence time at this enzyme, which might impact its duration of action in vivo. In order to gain insights into the kinetically different behaviors of the two inhibitors, an SMD study was carried out, which involved a careful optimization of the force and velocity parameters. We were able to identify two different binding pathways for the two inhibitors, as sunitinib exited the ATP binding site from the cavity entrance without a rupture point while sorafenib moved opposite to the ATP binding site entrance. Furthermore, the calculated ΔGoff values clearly reflect on a qualitative level the distinct off-rates of the two inhibitors, thus suggesting that this protocol could be tried on other VEGFR2 ligands to assess its robustness and then used to rank structural analogues of these derivatives.

Including ligand-induced protein flexibility into protein tunnel prediction

In proteins with buried active sites, understanding how ligands migrate through the tunnels that connect the exterior of the protein to the active site can shed light on substrate specificity and enzyme function. A growing body of evidence highlights the importance of protein flexibility in the binding site on ligand binding; however, the influence of protein flexibility throughout the body of the protein during ligand entry and egress is much less characterized. We have developed a novel tunnel prediction and evaluation method named IterTunnel, which includes the influence of ligand-induced protein flexibility, guarantees ligand egress, and provides detailed free energy information as the ligand proceeds along the egress route. IterTunnel combines geometric tunnel prediction with steered molecular dynamics in an iterative process to identify tunnels that open as a result of ligand migration and calculates the potential of mean force of ligand egress through a given tunnel. Applying this new method to cytochrome P450 2B6, we demonstrate the influence of protein flexibility on the shape and accessibility of tunnels. More importantly, we demonstrate that the ligand itself, while traversing through a tunnel, can reshape tunnels due to its interaction with the protein. This process results in the exposure of new tunnels and the closure of preexisting tunnels as the ligand migrates from the active site.

Structural and energetic analysis to provide insight residues of CYP2C9, 2C11 and 2E1 involved in valproic acid dehydrogenation selectivity

Docking and molecular dynamics (MD) simulation have been two computational techniques used to gain insight about the substrate orientation within protein active sites, allowing to identify potential residues involved in the binding and catalytic mechanisms. In this study, both methods were combined to predict the regioselectivity in the binding mode of valproic acid (VPA) on three cytochrome P-450 (CYP) isoforms CYP2C9, CYP2C11, and CYP2E1, which are involved in the biotransformation of VPA yielding reactive hepatotoxic intermediate 2-n-propyl-4-pentenoic acid (4nVPA). There are experimental data about hydrogen atom abstraction of the C4-position of VPA to yield 4nVPA, however, there are not structural evidence about the binding mode of VPA and 4nVPA on CYPs. Therefore, the complexes between these CYP isoforms and VPA or 4nVPA were studied to explore their differences in binding and energetic stabilization. Docking results showed that VPA and 4nVPA are coupled into CYPs binding site in a similar conformation, but it does not explain the VPA hydrogen atom abstraction. On the other hand, MD simulations showed a set of energetic states that reorient VPA at the first ns, then making it susceptible to a dehydrogenation reaction. For 4nVPA, multiple binding modes were observed in which the different states could favor either undergo other reaction mechanism or ligand expulsion from the binding site. Otherwise, the energetic and entropic contribution point out a similar behavior for the three CYP complexes, showing as expected a more energetically favorable binding free energy for the complexes between CYPs and VPA than with 4nVPA.

Modelling and enhanced molecular dynamics to steer structure-based drug discovery

The ever-increasing gap between the availabilities of the genome sequences and the crystal structures of proteins remains one of the significant challenges to the modern drug discovery efforts. The knowledge of structure-dynamics-functionalities of proteins is important in order to understand several key aspects of structure-based drug discovery, such as drug-protein interactions, drug binding and unbinding mechanisms and protein-protein interactions. This review presents a brief overview on the different state of the art computational approaches that are applied for protein structure modelling and molecular dynamics simulations of biological systems. We give an essence of how different enhanced sampling molecular dynamics approaches, together with regular molecular dynamics methods, assist in steering the structure based drug discovery processes.

Computational design of new Peptide inhibitors for amyloid Beta (aβ) aggregation in Alzheimer's disease: application of a novel methodology

Alzheimer's disease is the most common form of dementia. It is a neurodegenerative and incurable disease that is associated with the tight packing of amyloid fibrils. This packing is facilitated by the compatibility of the ridges and grooves on the amyloid surface. The GxMxG motif is the major factor creating the compatibility between two amyloid surfaces, making it an important target for the design of amyloid aggregation inhibitors. In this study, a peptide, experimentally proven to bind Aβ40 fibrils at the GxMxG motif, was mutated by a novel methodology that systematically replaces amino acids with residues that share similar chemical characteristics and subsequently assesses the energetic favorability of these mutations by docking. Successive mutations are combined and reassessed via docking to a desired level of refinement. This methodology is both fast and efficient in providing potential inhibitors. Its efficiency lies in the fact that it does not perform all possible combinations of mutations, therefore decreasing the computational time drastically. The binding free energies of the experimentally studied reference peptide and its three top scoring derivatives were evaluated as a final assessment/valuation. The potential of mean forces (PMFs) were calculated by applying the Jarzynski‚s equality to results of steered molecular dynamics simulations. For all of the top scoring derivatives, the PMFs showed higher binding free energies than the reference peptide substantiating the usage of the introduced methodology to drug design.

Unbinding pathways of GW4064 from human farnesoid X receptor as revealed by molecular dynamics simulations

Farnesoid X receptor (FXR, NR1H4) is a member of a nuclear receptor superfamily, which plays important roles in bile acid homeostasis, lipoprotein and glucose metabolism, and hepatic regeneration. GW4064 is a potent and selective FXR agonist and has become a tool compound to probe the physiological functions of FXR. Until now, the mechanism of GW4064 entering and leaving the FXR pocket is still poorly understood. Here, we report a computational study of GW4064 unbinding pathways from FXR by using several molecular dynamics (MD) simulation techniques. Based on the crystal structure of FXR in complex with GW4064, conventional MD was first used to refine the binding and check the stability of GW4064 in the FXR pocket. Random acceleration MD simulations were then performed to explore the possible unbinding pathways of GW4064 from FXR. Four main pathway clusters were found, among which three subpathways, namely Paths 2A, 2B, and 1B, were observed most frequently. Multiple steered MD simulations were further employed to estimate the maximum rupture force and the sum of the forces and to characterize the intermediate states of the ligand unbinding process. By comparing the average force profiles and structural changes, Paths 2A and 2B were identified to be the most favorable unbinding pathways. The former is located between the H1-H2 loop and the H5-H6 loop, and the latter is located in the cleft formed by the H5-H6 loop, H6, and H7. Moreover, the residues lining the pathways were analyzed for their roles in ligand unbinding. Based on our results, the possible structural modification strategies on GW4064 were also proposed.