Virtual Knockout Research Articles

Gene knockout inference with variational graph autoencoder learning single-cell gene regulatory networks.

In this paper, we introduce Gene Knockout Inference (GenKI), a virtual knockout (KO) tool for gene function prediction using single-cell RNA sequencing (scRNA-seq) data in the absence of KO samples when only wild-type (WT) samples are available. Without using any information from real KO samples, GenKI is designed to capture shifting patterns in gene regulation caused by the KO perturbation in an unsupervised manner and provide a robust and scalable framework for gene function studies. To achieve this goal, GenKI adapts a variational graph autoencoder (VGAE) model to learn latent representations of genes and interactions between genes from the input WT scRNA-seq data and a derived single-cell gene regulatory network (scGRN). The virtual KO data is then generated by computationally removing all edges of the KO gene-the gene to be knocked out for functional study-from the scGRN. The differences between WT and virtual KO data are discerned by using their corresponding latent parameters derived from the trained VGAE model. Our simulations show that GenKI accurately approximates the perturbation profiles upon gene KO and outperforms the state-of-the-art under a series of evaluation conditions. Using publicly available scRNA-seq data sets, we demonstrate that GenKI recapitulates discoveries of real-animal KO experiments and accurately predicts cell type-specific functions of KO genes. Thus, GenKI provides an in-silico alternative to KO experiments that may partially replace the need for genetically modified animals or other genetically perturbed systems.

Contribution of collagen degradation and proteoglycan depletion to cartilage degeneration in primary and secondary osteoarthritis: an in silico study

Current experimental approaches cannot elucidate the effect of maladaptive changes on the main cartilage constituents during the degeneration process in osteoarthritis (OA). In silico approaches, however, allow creating 'virtual knock-out' cases to elucidate these effects in a constituent-specific manner. We used such an approach to study the main mechanisms of cartilage degeneration in different mechanical loadings associated with the following OA etiologies: (1) physiological loading of degenerated cartilage, (2) injurious loading of healthy intact cartilage and (3) physiological loading of cartilage with a focal defect. We used the recently developed Cartilage Adaptive REorientation Degeneration (CARED) framework to simulate cartilage degeneration associated with primary and secondary OA (OA cases (1)-(3)). CARED incorporates numerical description of tissue-level cartilage degeneration mechanisms in OA, namely, collagen degradation, collagen reorientation, fixed charged density loss and tissue hydration increase following mechanical loading. We created 'virtual knock-out' scenarios by deactivating these degenerative processes one at a time in each of the three OA cases. In the injurious loading of intact and physiological loading of degenerated cartilage, collagen degradation drives degenerative changes through fixed charge density loss and tissue hydration rise. In contrast, the two later mechanisms were more prominent in the focal defect cartilage model. The virtual knock-out models reveal that injurious loading to intact cartilage and physiological loading to degenerated cartilage induce initial degenerative changes in the collagen network, whereas, in the presence of a focal cartilage defect, mechanical loading initially causes proteoglycans (PG) depletion, before changes in the collagen fibril network occur.

Ion-channel degeneracy and heterogeneities in the emergence of complex spike bursts in CA3 pyramidal neurons.

Complex spike bursting (CSB) is a characteristic electrophysiological signature exhibited by several neuronal subtypes and has been implicated in neural plasticity, learning, perception, anaesthesia and active sensing. Here, we address how pronounced intrinsic and synaptic heterogeneities affect CSB, with hippocampal CA3 pyramidal neurons (CA3PNs), where CSB emergence and heterogeneities are well characterized, as a substrate. We randomly generated 12,000 unique models and found 236 valid models that satisfied 11 characteristic CA3PN measurements. These morphologically and biophysically realistic valid models accounted for gating kinetics and somatodendritic expression profiles of 10 active ion channels. This heterogeneous population of valid models was endowed with broad distributions of underlying parameters showing weak pairwise correlations. We found two functional subclasses of valid models, intrinsically bursting and regular spiking, with significant differences in the expression of calcium and calcium-activated potassium conductances. We triggered CSB in all 236models through different intrinsic or synaptic protocols and observed considerable heterogeneity in CSB propensity and properties spanning models and protocols. Finally, we used virtual knockout analyses and showed that synergistic interactions between intrinsic and synaptic mechanisms regulated CSB emergence and dynamics. Specifically, although there was a dominance of calcium and calcium-activated potassium channels in the emergence of CSB, individual deletion of none of the several ion channels or N-methyl-d-aspartate receptors resulted in the complete elimination of CSB across all models. Together, our analyses critically implicate ion-channel degeneracy in the robust emergence of CSB and other characteristic signatures of CA3PNs, despite pronounced heterogeneities in underlying intrinsic and synaptic properties. KEY POINTS: An unbiased stochastic search algorithm yielded a heterogeneous population of morphologically and biophysically realistic CA3 pyramidal neuronal models matching several signature electrophysiological characteristics. Two functional subclasses of valid models were identified with intrinsically bursting (IB) and regular spiking (RS) characteristics, which exhibited differential localization within the parametric space with linear and non-linear dimension reduction analyses. Calcium and calcium-activated potassium channels distinguished IB from RS models, apart from playing dominant roles in the emergence of complex spike bursting (CSB). The impact of deleting individual ion channels or N-methyl-d-aspartate receptors was variable across different models and differential for each channel/receptor, pointing to ion-channel degeneracy in the emergence of CSB. Biological heterogeneities across different neurons of the same subtype, ion-channel degeneracy and state-dependent changes (involving activity-dependent plasticity, pathology, and neuromodulation of intrinsic and synaptic properties) need to be considered carefully in assessing the propensity and dynamicsof CSB in different neuronal subtypes.

Voltage-Gated Ion Channels and the Variability in Information Transfer.

The prerequisites for neurons to function within a circuit and be able to contain and transfer information efficiently and reliably are that they need to be homeostatically stable and fire within a reasonable range, characteristics that are governed, among others, by voltage-gated ion channels (VGICs). Nonetheless, neurons entail large variability in the expression levels of VGICs and their corresponding intrinsic properties, but the role of this variability in information transfer is not fully known. In this study, we aimed to investigate how this variability of VGICs affects information transfer. For this, we used a previously derived population of neuronal model neurons, each with the variable expression of five types of VGICs, fast Na+, delayed rectifier K+, A-type K+, T-type Ca++, and HCN channels. These analyses showed that the model neurons displayed variability in mutual information transfer, measured as the capability of neurons to successfully encode incoming synaptic information in output firing frequencies. Likewise, variability in the expression of VGICs caused variability in EPSPs and IPSPs amplitudes, reflected in the variability of output firing frequencies. Finally, using the virtual knockout methodology, we show that among the ion channels tested, the A-type K+ channel is the major regulator of information processing and transfer.

Dynamic expression of Ddc mediates the melatonin biosynthesis rhythms in the mouse: a virtual knockout approach

Dynamic expression of Ddc mediates the melatonin biosynthesis rhythms in the mouse: a virtual knockout approach

015 Modulating melatonin dynamics at transcription level using virtual knockout approaches: an advanced perspective in sleep medicine

Abstract Introduction Sleep disorders, the most neglected public-health issues, are threatening overall health. It is tightly associated with the individual’s exposures to the light/dark (LD)-cycles linked to their circadian rhythms. Lifestyle, shift-work, frequent travels, and post-pandemic-stress lead unintentional compromise of sleep, thus circadian homeostasis. Melatonin (MT), a pivotal natural hormone for circadian and sleep health, attains acrophase in the dark. MT mediates LD-triggered circadian rhythms through its dynamic expressions. Circadian phases are greatly reflected by MT-dynamics. Dim-light-MT-onsets (DLMO) act as a marker, reporting internal circadian-timing in mammals. Estimating this is essential in therapeutic-designing against misaligned circadian conditions. Despite many experimental approaches, there is still a slit hacking the MT-dynamics from molecules to systems. Inclusive perspectives on endogenous factors affecting MT’s synthesis, secretions and bioavailability over time-course are not extensively exposed. MT-dynamics has multiplexed stochastic interactions across numerous genes, TFs, and regulators, and they are coupled non-linearly. Small changes used to compound through the genetic networks and reflected in systems-wide events marking distinct signalling response dynamics. Understanding such responses is challenging yet imperative. A robust quantitative model is inevitable to investigate such stochastic intricacy. Methods We proposed a quantitative framework to model MT signalling networks using diverse kinetic parameters linked in its genetic circuits and perturbing them must alter the MT-dynamics. We used a robust computational approach, LogicTRN to decode the systematic controls of the MT-dynamics. It combines multi-layered transcriptome-wide data as input. Computing this returned the regulatory TF-logics in the transcriptional regulatory networks for MT. We developed transcriptional simulations with virtual-knockout mutants and performed genetic network perturbation study. Results The results showed the reconstruction of robust quantitative regulatory networks decrypting transcriptional controls for MT-dynamics to estimate the influence of the multiple kinetically distinct inputs affecting those dynamics. This offered competitive advantages in terms of scalability, robustness, and iterations to characterize the effective molecular-targets to modulate the genetic circuit of MT-dynamics effectually. Conclusion Quantitative reconstruction and characterization of the regulatory interactome of MT may facilitate us to strategize the adjustments of regulatory controls to effectively modulate MT-dynamics. This foundation may enhance the advancement of circadian and sleep medicine in future. Support (if any):

Identifying Transcription Factor Combinations to Modulate Circadian Rhythms by Leveraging Virtual Knockouts on Transcription Networks.

SummaryThe mammalian circadian systems consist of indigenous, self-sustained 24-h rhythm generators. They comprise many genes, molecules, and regulators. To decode their systematic controls, a robust computational approach was employed. It integrates transcription-factor-occupancy and time-series gene-expression data as input. The model equations were constructed and solved to determine the transcriptional regulatory logics in the mouse transcriptome network. This hypothesizes to explore the underlying mechanisms of combinatorial transcriptional regulations for circadian rhythms in mouse. We reconstructed the quantitative transcriptional-regulatory networks for circadian gene regulation at a dynamic scale. Transcriptional-simulations with virtually knocked-out mutants were performed to estimate their influence on networks. The potential transcriptional-regulators-combinations modulating the circadian rhythms were identified. Of them, CLOCK/CRY1 double knockout preserves the highest modulating capacity. Our quantitative framework offers a quick, robust, and physiologically relevant way to characterize the druggable targets to modulate the circadian rhythms at a dynamic scale effectively.

Degeneracy in the emergence of spike-triggered average of hippocampal pyramidal neurons

Hippocampal pyramidal neurons are endowed with signature excitability characteristics, exhibit theta-frequency selectivity — manifesting as impedance resonance and as a band-pass structure in the spike-triggered average (STA) — and coincidence detection tuned for gamma-frequency inputs. Are there specific constraints on molecular-scale (ion channel) properties in the concomitant emergence of cellular-scale encoding (feature detection and selectivity) and excitability characteristics? Here, we employed a biophysically-constrained unbiased stochastic search strategy involving thousands of conductance-based models, spanning 11 active ion channels, to assess the concomitant emergence of 14 different electrophysiological measurements. Despite the strong biophysical and physiological constraints, we found models that were similar in terms of their spectral selectivity, operating mode along the integrator-coincidence detection continuum and intrinsic excitability characteristics. The parametric combinations that resulted in these functionally similar models were non-unique with weak pair-wise correlations. Employing virtual knockout of individual ion channels in these functionally similar models, we found a many-to-many relationship between channels and physiological characteristics to mediate this degeneracy, and predicted a dominant role for HCN and transient potassium channels in regulating hippocampal neuronal STA. Our analyses reveals the expression of degeneracy, that results from synergistic interactions among disparate channel components, in the concomitant emergence of neuronal excitability and encoding characteristics.

Robust emergence of sharply tuned place-cell responses in hippocampal neurons with structural and biophysical heterogeneities.

Hippocampal pyramidal neurons sustain propagation of fast electrical signals and are electrotonically non-compact structures exhibiting cell-to-cell variability in their complex dendritic arborization. In this study, we demonstrate that sharp place-field tuning and several somatodendritic functional maps concomitantly emerge despite the presence of geometrical heterogeneities in these neurons. We establish this employing an unbiased stochastic search strategy involving thousands of models that spanned several morphologies and distinct profiles of dispersed synaptic localization and channel expression. Mechanistically, employing virtual knockout models (VKMs), we explored the impact of bidirectional modulation in dendritic spike prevalence on place-field tuning sharpness. Consistent with the prior literature, we found that across all morphologies, virtual knockout of either dendritic fast sodium channels or N-methyl-D-aspartate receptors led to a reduction in dendritic spike prevalence, whereas A-type potassium channel knockouts resulted in a non-specific increase in dendritic spike prevalence. However, place-field tuning sharpness was critically impaired in all three sets of VKMs, demonstrating that sharpness in feature tuning is maintained by an intricate balance between mechanisms that promote and those that prevent dendritic spike initiation. From the functional standpoint of the emergence of sharp feature tuning and intrinsic functional maps, within this framework, geometric variability was compensated by a combination of synaptic democracy, the ability of randomly dispersed synapses to yield sharp tuning through dendritic spike initiation, and ion-channel degeneracy. Our results suggest electrotonically non-compact neurons to be endowed with several degrees of freedom, encompassing channel expression, synaptic localization and morphological microstructure, in achieving sharp feature encoding and excitability homeostasis.

Effects of HCN2 Mutations on Dendritic Excitability and Synaptic Plasticity: A Computational Study

Several reports of augmented hyperpolarisation-activated cyclic nucleotide-gated (HCN) currents in seizures have suggested a pro-convulsive identity for HCN channels. The mutations identified in one or more of the four HCN channel subunits are found to be contributing to different epileptic phenotypes. S126L, S632W, V246M and E515K are four different mutations affecting the HCN2 subunit and have been reported in febrile seizures and partial/generalised idiopathic epilepsies. From the visible outcomes in subjects with these mutations, it is evident that they must play important roles in altering dendritic excitability. Through this simulation study using NEURON, we created a three-compartmental, hippocampal CA1 pyramidal neuron synapse model expressing seven different ion channels (fast sodium (NaF), T-type calcium (CaT), R-type calcium (CaR), delayed rectifier potassium (KDR), A-type potassium (KA), small conductance potassium (SK), and HCN channels) and two glutamate receptors (AMPAR and NMDAR). We modelled an HCN2 channel and incorporated changes in it to obtain mutation kinetics. Their effects on excitability were studied by observing resting membrane potentials, input resistances and plasticity profiles for measuring the sliding modification threshold (SMT) of Bienenstock–Cooper–Munro (BCM) theory. Virtual knockouts of ion channels other than HCN were also performed to assess their role in altering excitability when they act alongside HCN2 mutations. Our results show that HCN2 mutations can potentially be a primary causative factor for excessive action potential firing through their effect on resting membrane potentials and input resistance.

Spatially dispersed synapses yield sharply-tuned place cell responses through dendritic spike initiation.

Key points The generation of dendritic spikes and the consequent sharp tuning of neuronal responses are together attainable even when iso‐feature synapses are randomly dispersed across the dendritic arbor.Disparate combinations of channel conductances with distinct configurations of randomly dispersed place field synapses concomitantly yield similar sharp tuning profiles and similar functional maps of several intrinsic properties.Targeted synaptic plasticity converts silent cells to place cells for specific place fields in models with disparate channel combinations that receive dispersed synaptic inputs from multiple place field locations.Dispersed localization of iso‐feature synapses is a strong candidate for achieving sharp feature selectivity in neurons across sensory‐perceptual systems, with several degrees of freedom in relation to synaptic locations.Quantitative evidence for the possibility that degeneracy (i.e. the ability of disparate structural components to yield similar functional outcomes) could act as a broad framework that effectively accomplishes the twin goals of input‐feature encoding and homeostasis of intrinsic properties without cross interferences. A prominent hypothesis spanning several sensory‐perceptual systems implicates spatially clustered synapses in the generation of dendritic spikes that mediate sharply‐tuned neuronal responses to input features. In this conductance‐based morphologically‐precise computational study, we tested this hypothesis by systematically analysing the impact of distinct synaptic and channel localization profiles on sharpness of spatial tuning in hippocampal pyramidal neurons. We found that the generation of dendritic spikes, the emergence of an excitatory ramp in somatic voltage responses, the expression of several intrinsic somatodendritic functional maps and sharp tuning of place‐cell responses were all attainable even when iso‐feature synapses are randomly dispersed across the dendritic arbor of models with disparate channel combinations. Strikingly, the generation and propagation of dendritic spikes, reliant on dendritic sodium channels and N‐methyl‐d‐asparate receptors, mediated the sharpness of spatial tuning achieved with dispersed synaptic localization. To ensure that our results were not artefacts of narrow parametric choices, we confirmed these conclusions with independent multiparametric stochastic search algorithms spanning thousands of unique models for each synaptic localization scenario. Next, employing virtual knockout models, we demonstrated a vital role for dendritically expressed voltage‐gated ion channels, especially the transient potassium channels, in maintaining sharpness of place‐cell tuning. Importantly, we established that synaptic potentiation targeted to afferents from one specific place field was sufficient to impart place field selectivity even when intrinsically disparate neurons received randomly dispersed afferents from multiple place field locations. Our results provide quantitative evidence for disparate combinations of channel and synaptic localization profiles to concomitantly yield similar tuning and similar intrinsic properties.

Degeneracy in the regulation of short-term plasticity and synaptic filtering by presynaptic mechanisms.

We develop a new biophysically rooted, physiologically constrained conductance-based synaptic model to mechanistically account for short-term facilitation and depression, respectively through residual calcium and transmitter depletion kinetics. We address the specific question of how presynaptic components (including voltage-gated ion channels, pumps, buffers and release-handling mechanisms) and interactions among them define synaptic filtering and short-term plasticity profiles. Employing global sensitivity analyses (GSAs), we show that near-identical synaptic filters and short-term plasticity profiles could emerge from disparate presynaptic parametric combinations with weak pairwise correlations. Using virtual knockout models, a technique to address the question of channel-specific contributions within the GSA framework, we unveil the differential and variable impact of each ion channel on synaptic physiology. Our conclusions strengthen the argument that parametric and interactional complexity in biological systems should not be viewed from the limited curse-of-dimensionality standpoint, but from the evolutionarily advantageous perspective of providing functional robustness through degeneracy. Information processing in neurons is known to emerge as a gestalt of pre- and post-synaptic filtering. However, the impact of presynaptic mechanisms on synaptic filters has not been quantitatively assessed. Here, we developed a biophysically rooted, conductance-based model synapse that was endowed with six different voltage-gated ion channels, calcium pumps, calcium buffer and neurotransmitter-replenishment mechanisms in the presynaptic terminal. We tuned our model to match the short-term plasticity profile and band-pass structure of Schaffer collateral synapses, and performed sensitivity analyses to demonstrate that presynaptic voltage-gated ion channels regulated synaptic filters through changes in excitability and associated calcium influx. These sensitivity analyses also revealed that calcium- and release-control mechanisms were effective regulators of synaptic filters, but accomplished this without changes in terminal excitability or calcium influx. Next, to perform global sensitivity analysis, we generated 7000 randomized models spanning 15 presynaptic parameters, and computed eight different physiological measurements in each of these models. We validated these models by applying experimentally obtained bounds on their measurements, and found 104 (∼1.5%) models to match the validation criteria for all eight measurements. Analysing these valid models, we demonstrate that analogous synaptic filters emerge from disparate combinations of presynaptic parameters exhibiting weak pairwise correlations. Finally, using virtual knockout models, we establish the variable and differential impact of different presynaptic channels on synaptic filters, underlining the critical importance of interactions among different presynaptic components in defining synaptic physiology. Our results have significant implications for protein-localization strategies required for physiological robustness and for degeneracy in long-term synaptic plasticity profiles.

Comparative analysis of metabolic machinery of Frankia along with other selected actinobacteria

Actinobacteria exhibits a wide range of adaptive strategies by adjusting their transcriptional and metabolic profiles for optimum utilization of available resources. Thus, a proper understanding of metabolic pathways along with their constituent enzymes may provide vital clues for survival strategies engaged by these bacteria. In the present study, we have compared the complete metabolic contour of five Frankia strains along with twelve other actinobacteria including pathogenic and non-pathogenic strains of Mycobacterium and Streptomyces. Among the Frankia strains, EAN1pec and Eul1c have the highest number of distinct metabolic enzymes while Candidatus Frankia datiscae Dg1 has the least. Frankia strains share 383 metabolic enzymes among themselves while 244 enzymes have been identified to be shared by all the studied strains. We also identified unique/maker enzymes in each of the chosen strains. Among Frankia, CcI3 bears the highest number of unique enzymes whereas Mycobacterium vanbaalenii has maximum number overall. Cluster analysis was used to explore the effluxes in crucial metabolic pathways. The analysis reveals that actinobacteria exhibit diverse routes for metabolizing substrates. Genome scale metabolic models of Frankia alni ACN14a, Streptomyces coelicolor A3 (2), and Mycobacterium tuberculosis H37Rv were utilized for analyzing metabolic capabilities based on Flux balance analysis (FBA) approach. Simulation of virtual knockouts of genes in metabolic network helped in inferring essentiality of metabolic genes and their encoded enzymes. The present study provides an overview of the metabolic capability of some actinobacteria strains and may have further implications for systematically designing novel strategies for improvement of such strains.

A molecular systems approach to modelling human skin pigmentation: identifying underlying pathways and critical components.

BackgroundUltraviolet radiations (UV) serve as an environmental stress for human skin, and result in melanogenesis, with the pigment melanin having protective effects against UV induced damage. This involves a dynamic and complex regulation of various biological processes that results in the expression of melanin in the outer most layers of the epidermis, where it can exert its protective effect. A comprehensive understanding of the underlying cross talk among different signalling molecules and cell types is only possible through a systems perspective. Increasing incidences of both melanoma and non-melanoma skin cancers necessitate the need to better comprehend UV mediated effects on skin pigmentation at a systems level, so as to ultimately evolve knowledge-based strategies for efficient protection and prevention of skin diseases.MethodsA network model for UV-mediated skin pigmentation in the epidermis was constructed and subjected to shortest path analysis. Virtual knock-outs were carried out to identify essential signalling components.ResultsWe describe a network model for UV-mediated skin pigmentation in the epidermis. The model consists of 265 components (nodes) and 429 directed interactions among them, capturing the manner in which one component influences the other and channels information. Through shortest path analysis, we identify novel signalling pathways relevant to pigmentation. Virtual knock-outs or perturbations of specific nodes in the network have led to the identification of alternate modes of signalling as well as enabled determining essential nodes in the process.ConclusionsThe model presented provides a comprehensive picture of UV mediated signalling manifesting in human skin pigmentation. A systems perspective helps provide a holistic purview of interconnections and complexity in the processes leading to pigmentation. The model described here is extensive yet amenable to expansion as new data is gathered. Through this study, we provide a list of important proteins essential for pigmentation which can be further explored to better understand normal pigmentation as well as its pathologies including vitiligo and melanoma, and enable therapeutic intervention.Electronic supplementary materialThe online version of this article (doi:10.1186/s13104-015-1128-6) contains supplementary material, which is available to authorized users.

Analogous synaptic plasticity profiles emerge from disparate channel combinations.

An open question within the Bienenstock-Cooper-Munro theory for synaptic modification concerns the specific mechanism that is responsible for regulating the sliding modification threshold (SMT). In this conductance-based modeling study on hippocampal pyramidal neurons, we quantitatively assessed the impact of seven ion channels (R- and T-type calcium, fast sodium, delayed rectifier, A-type, and small-conductance calcium-activated (SK) potassium and HCN) and two receptors (AMPAR and NMDAR) on a calcium-dependent Bienenstock-Cooper-Munro-like plasticity rule. Our analysis with R- and T-type calcium channels revealed that differences in their activation-inactivation profiles resulted in differential impacts on how they altered the SMT. Further, we found that the impact of SK channels on the SMT critically depended on the voltage dependence and kinetics of the calcium sources with which they interacted. Next, we considered interactions among all the seven channels and the two receptors through global sensitivity analysis on 11 model parameters. We constructed 20,000 models through uniform randomization of these parameters and found 360 valid models based on experimental constraints on their plasticity profiles. Analyzing these 360 models, we found that similar plasticity profiles could emerge with several nonunique parametric combinations and that parameters exhibited weak pairwise correlations. Finally, we used seven sets of virtual knock-outs on these 360 models and found that the impact of different channels on the SMT was variable and differential. These results suggest that there are several nonunique routes to regulate the SMT, and call for a systematic analysis of the variability and state dependence of the mechanisms underlying metaplasticity during behavior and pathology.

In Silico Modeling for the Nonlinear Absorption Kinetics of UK-343,664: A P-gp and CYP3A4 Substrate

The aim of this work was to extrapolate in vitro and preclinical animal data to simulate the pharmacokinetic parameters of UK-343,664, a P-glycoprotein (P-gp) and CYP3A4 substrate, in human. In addition, we aimed to develop a simulation model to demonstrate the involvement and the controversial complex interaction of intestinal P-gp and CYP3A4 in its nonlinear absorption, first-pass extraction, and pharmacokinetics using the advanced compartmental absorption and transit (ACAT) model. Finally, we aimed to compare the results predicted from the model to the reported findings in human clinical studies. In situ perfusion, allometric scaling, PBPK Rodger mechanistic approach, in vitro metabolism, and fitting to in vivo data were used to mechanistically explain the absorption, distribution and metabolism, respectively. GastroPlus was used to build the integrated simulation model in human for UK-343,664 to mechanistically explain the observed clinical data at 30, 100, 200, 400, and 800 mg oral doses. The measured in vitro value for CYP3A4 K(m) (465 μM) in rCYPs was converted to units of μg/mL, corrected for assumed microsomal binding (17.8%) and applied to all metabolic processes. The measured in vitro values of V(max) for CYP3A4 (38.9 pmol/min/pmol), 2C8, 2C9, 2C19, and 2D6 were used along with the in vitro CYP3A4 K(m) to simulate liver first pass extraction and systemic clearance. The measured in vitro values of V(max) for CYP3A4 and 2D6 were used along with the in vitro CYP3A4 K(m) to simulate gut first pass extraction. V(max) and K(m) values for P-gp were obtained by fitting to in vivo data and used to simulate gut efflux transport activity. Investigation of the interaction mechanism of P-gp and CYP3A4 in the intestine was achieved by comparing the influence of a virtual knockout of P-gp or gut metabolism on the fraction absorbed, fraction reaching the portal vein, and fraction metabolized in the gut. Comparison between simulation and in vivo results showed that the in silico simulation provided a mechanistic explanation of the observed nonlinear absorption kinetics of UK-343,664 in human following its administration in the range of 30-800 mg as oral solutions. The simulation results of the pharmacokinetic parameters, AUC and C(max), by GastroPlus were comparable with those observed in vivo. This simulation model is one possible mechanistic explanation of the observed in vivo data and suggests that the nonlinear dose dependence could be attributed to saturation of both the efflux transport by P-gp and the intestinal metabolism. However, the concentration ranges for either protein saturation did not overlap and resulted in much greater than dose proportional increases in AUC. At low doses, producing intraenterocyte concentrations below the fitted value of K(m) for P-gp, the influence of P-gp appears to be protective and results in a lower fraction of gut 3A4 metabolism. At higher doses, as P-gp becomes saturated the fraction of gut 3A4 extraction increases, and eventually at the highest doses, where 3A4 becomes saturated, the fraction of gut 3A4 extraction again decreases. Such a complex interpretation of this in vitro-in vivo extrapolation (IVIVE) is another example of the value and insight obtained by physiologically based absorption simulation.

Extended CADLIVE: a novel graphical notation for design of biochemical network maps and computational pathway analysis

Biochemical network maps are helpful for understanding the mechanism of how a collection of biochemical reactions generate particular functions within a cell. We developed a new and computationally feasible notation that enables drawing a wide resolution map from the domain-level reactions to phenomenological events and implemented it as the extended GUI network constructor of CADLIVE (Computer-Aided Design of LIVing systEms). The new notation presents ‘Domain expansion’ for proteins and RNAs, ‘Virtual reaction and nodes’ that are responsible for illustrating domain-based interaction and ‘InnerLink’ that links real complex nodes to virtual nodes to illustrate the exact components of the real complex. A modular box is also presented that packs related reactions as a module or a subnetwork, which gives CADLIVE a capability to draw biochemical maps in a hierarchical modular architecture. Furthermore, we developed a pathway search module for virtual knockout mutants as a built-in application of CADLIVE. This module analyzes gene function in the same way as molecular genetics, which simulates a change in mutant phenotypes or confirms the validity of the network map. The extended CADLIVE with the newly proposed notation is demonstrated to be feasible for computational simulation and analysis.