Systems science, also referred to as systems research or simply systems, is a transdisciplinary field that is concerned with understanding simple and complex systems in nature and society, which leads to the advancements of formal, natural, social, and applied attributions throughout engineering, technology, and science itself.
To systems scientists, the world can be understood as a system of systems. The field aims to develop transdisciplinary foundations that are
applicable in a variety of areas, such as psychology, biology, medicine,
communication, business, technology, computer science, engineering, and
social sciences.
Themes commonly stressed in system science are (a) holistic view, (b) interaction between a system and its embedding environment,
and (c) complex (often subtle) trajectories of dynamic behavior that
sometimes are stable (and thus reinforcing), while at various 'boundary conditions'
can become wildly unstable (and thus destructive). Concerns about
Earth-scale biosphere/geosphere dynamics is an example of the nature of
problems to which systems science seeks to contribute meaningful
insights.
Associated fields
The systems sciences are a broad array of fields. One way
of conceiving of these is in three groups: fields that have developed
systems ideas primarily through theory; those that have done so
primarily through practical engagements with problem situations; and
those that have applied ideas for other disciplines.
The soft systems methodology was developed in England by academics at the University of Lancaster Systems Department through a ten-year action research programme. The main contributor is Peter Checkland
(born 18 December 1930, in Birmingham, UK), a British management
scientist and emeritus professor of systems at Lancaster University.
Systems analysis branch of systems science that analyzes
systems, the interactions within those systems, or interaction with its
environment, often prior to their automation as computer models. Systems analysis is closely associated with the RAND corporation.
System dynamics is an approach to understanding the behavior of complex systems over time. It offers "simulation technique for modeling business and social systems", which deals with internal feedback loops and time delays that affect
the behavior of the entire system. What makes using system dynamics
different from other approaches to studying complex systems is the use
of feedback loops and stocks and flows.
Systems engineering (SE) is an interdisciplinary field of engineering, that focuses on the development and organization of complex systems. It is the "art and science of creating whole solutions to complex problems", for example: signal processing systems, control systems and communication system, or other forms of high-level modelling and design in specific fields of engineering. Systems Science is foundational to the Embedded Software Development that is founded in the embedded requirements of Systems Engineering.
Cytochromes P450 (P450s or CYPs) are a superfamily of enzymes containing heme as a cofactor that mostly, but not exclusively, function as monooxygenases. However, they are not omnipresent; for example, they have not been found in Escherichia coli. In mammals, these enzymes oxidize steroids, fatty acids, xenobiotics, and participate in many biosyntheses. By hydroxylation, CYP450 enzymes convert xenobiotics into hydrophilic derivatives, which are more readily excreted.
The most common reaction catalyzed by cytochromes P450 is a
monooxygenase reaction, e.g., insertion of one atom of oxygen into the
aliphatic position of an organic substrate (RH), while the other oxygen
atom is reduced to water:
RH + O2 + NADPH + H+ → ROH + H2O + NADP+
Classification
Nomenclature
Genes encoding P450 enzymes, and the enzymes themselves, are designated with the root symbolCYP for the superfamily, followed by a number indicating the gene family, a capital letter indicating the subfamily, and another numeral for the individual gene. The convention is to italicize the name when referring to the gene. For example, CYP2E1 is the gene that encodes the enzyme CYP2E1—one of the enzymes involved in paracetamol (acetaminophen) metabolism. The CYP nomenclature is the official naming convention, although occasionally CYP450 or CYP450
is used synonymously. These names should never be used as according to
the nomenclature convention (as they denote a P450 in family number
450). However, some gene or enzyme names for P450s are also referred to
by historical names (e.g. P450BM3 for CYP102A1) or
functional names, denoting the catalytic activity and the name of the
compound used as substrate. Examples include CYP5A1, thromboxane A2 synthase, abbreviated to TBXAS1 (thromboxane A2 synthase 1), and CYP51A1,
lanosterol 14-α-demethylase, sometimes unofficially abbreviated to LDM
according to its substrate (lanosterol) and activity (demethylation).
The nomenclature guidelines suggest that members of new CYP families share at least 40% amino-acid
identity, while members of subfamilies must share at least 55%
amino-acid identity. Nomenclature committees assign and track both base
gene names (Cytochrome P450 HomepageArchived 2010-06-27 at the Wayback Machine) and allele names (CYP Allele Nomenclature Committee). These similarity-based groupings are frequently recovered in
phylogenetic analyses and members generally share features in their
catalytic activities. Sometimes the suggested similarity thresholds do
not exactly match what phylogenetic patterns show (e.g. a new member
that is close to a family but only 39% identical), causing what is known
as "family creep" as the similarity threshold is reduced, or the
occasional split of families.
There is a universal nomenclature for the assignment of P450 family numbers across the taxonomic groups:
CYP1–49, CYP301–CYP499, ...: Animals
CYP440–446: Reserved for CYP74 clan members found in animals
CYP51–69, CYP501–CYP699, ...: Fungi and Lower Eukaryotes
CYP6001–CYP6099: Fungal fusions of P450s with other enzymes, e.g. dioxygenases or peroxygenases or isomerases.
The taxonomic group blocks are defined for CYP1001–CYP69999 by stretching the taxonomic blocks defined for CYP101–999. For example, CYP3001–4999 and CYP30001–CYP49999 are allocated to animals. The reservations defined under these groups are not stretched. Several databases are available for the tracking of defined P450 family numbers, subfamily letters, and ortholog group numbers, with the intention that not only there is no ambiguity in what each family-subfamily prefix means, but also that identically-named genes across different species are orthologous to each other. As of April2026,
the most complete database is the P450 Atlas (version 1.3.0) covering
11068 families, 26037 subfamilies, 79577 ortholog groups and 164068
example sequences of ortholog groups.
Comparison between many P450 enzymes of different families give rise to the concept of clans,
evolutionary grouping of families. The exact similarity cut-off is
poorly defined, but it is generally understood that it should derive
from a few first-diverging nodes of a phylogenetic tree. Some clans only have one family while others are highly diversified
with many families within (e.g. CYP71-clan and CYP85-clan). Tracking the
emergence of clans and families across many taxonomic groups paints a
vivid picture of the evolution of metabolic capabilities.
Microsomal P450 systems in which electrons are transferred from NADPH via a CPR (variously CPR, POR, or CYPOR).
Also found in bacteria such as the P450meg (CYP106A2) from Bacillus megaterium.
Fr/Fd/P450 systems which employ a ferredoxin reductase and a ferredoxin to transfer electrons to P450. A representative is the plant plastid P450cam (CYP101A1) system from the CAM operon for camphor-related substrates.
Mitochondrial P450 systems which employ adrenodoxin reductase and adrenodoxin (a ferrodoxin) to transfer electrons from NADPH to P450.
FMN/Fd/P450 systems: originally found in Rhodococcus species, in which a FMN-domain-containing reductase is fused to the CYP.
CYB5R/cyb5/P450 systems in which both electrons required by the CYP come from cytochrome b5, which is in turn reduced by cytochrome b5 reductase (CYB5R).
The "Fe(V) intermediate" at the bottom left is a simplification: it is an Fe(IV) with a radical heme ligand.
Structure
The active site of cytochrome P450 contains a heme-iron center. The iron is tethered to the protein via a cysteinethiolateligand. This cysteine and several flanking residues are highly conserved in known P450s, and have the formal PROSITE signature consensus pattern [FW] - [SGNH] - x - [GD] - {F} - [RKHPT] - {P} - C - [LIVMFAP] - [GAD]. In general, the P450 catalytic cycle proceeds as follows:
Catalytic cycle
Substrate binds in proximity to the heme group,
on the side opposite to the axial thiolate. Substrate binding induces a
change in the conformation of the active site, often displacing a water
molecule from the distal axial coordination position of the heme iron, and changing the state of the heme iron from low-spin to high-spin.
Substrate binding induces electron transfer from NAD(P)H via cytochrome P450 reductase or another associated reductase, converting Fe(III) to Fe(II).
Molecular oxygen binds to the resulting ferrous heme center at the distal axial coordination position, initially giving a dioxygen adduct similar to oxy-myoglobin.
The peroxo group formed in step 4 is rapidly protonated
twice, releasing one molecule of water and forming the highly reactive
species referred to as P450 Compound 1 (or just Compound I). This highly reactive intermediate was isolated in 2010, P450 Compound 1 is an iron(IV) oxo (or ferryl) species with an additional oxidizing equivalent delocalized over the porphyrin and thiolate ligands. Evidence for the alternative perferryl iron(V)-oxo is lacking.
Oxygen rebound mechanism
utilized by cytochrome P450 for conversion of hydrocarbons to alcohols
via the action of "compound I", an iron(IV) oxide bound to a heme
radical cation.
Depending on the substrate and enzyme involved, P450
enzymes can catalyze any of a wide variety of reactions. A hypothetical
hydroxylation is illustrated. After the hydroxylated product has been
released from the active site, the enzyme returns to its original state,
with a water molecule returning to occupy the distal coordination
position of the iron nucleus.
An alternative route for mono-oxygenation is via the
"peroxide shunt" (path "S" in figure). This pathway entails oxidation of
the ferric-substrate complex with oxygen-atom donors such as peroxides
and hypochlorites. A hypothetical peroxide "XOOH" is shown in the diagram.
Mechanistic details, including the oxygen rebound mechanism, have been investigated with synthetic analogues, consisting of iron oxo heme complexes.
Spectroscopy
Binding of substrate is reflected in the spectral properties of the enzyme, with an increase in absorbance at 390nm and a decrease at 420nm. This can be measured by difference spectroscopies and is referred to as the "typeI"
difference spectrum (see inset graph in figure). Some substrates cause
an opposite change in spectral properties, a "reverse typeI"
spectrum, by processes that are as yet unclear. Inhibitors and certain
substrates that bind directly to the heme iron give rise to the typeII difference spectrum, with a maximum at 430nm and a minimum at 390nm
(see inset graph in figure). If no reducing equivalents are available,
this complex may remain stable, allowing the degree of binding to be
determined from absorbance measurements in vitro C: If carbon monoxide (CO) binds to reduced P450, the catalytic cycle is
interrupted. This reaction yields the classic CO difference spectrum
with a maximum at 450nm.
However, the interruptive and inhibitory effects of CO varies upon
different CYPs such that the CYP3A family is relatively less affected.
Binding site
The
conserved sequence of cytochrome P450 is highlighted, depicting how
specific amino acid residues are essential for binding to a heme. In
cytochrome p450 as seen in Streptomyces antibioticus (PDB code 4XE3), Phe349, Gly352, Ala353, Cys356, and Gly358 represent the conserved domain.
The heme in cytochrome P450 binds to a conserved sequence: FxxGxRxCxG,
where "x" denotes some variant amino acid. The cysteine (C) binds iron
and arginine (R), forming strong electrostatic interactions with
negatively charged side chains of the heme. The glycine (G) residues
within the conserved sequence are essential, as their small structure
enables surrounding alpha helices to remain in place without interacting
with a variant amino acid. Additional conserved motifs are:
ExxR (K-helix)
AGxDTT (I-helix, oxygen-binding domain)
Other hydroxylation enzymes
Many hydroxylation reactions (insertion of hydroxyl groups) use CYP enzymes, but many other hydroxylases exist. Alpha-ketoglutarate-dependent hydroxylases
also rely on an Fe=O intermediate but lack hemes. Methane
monooxygenase, which converts methane to methanol, are non-heme iron-and
iron-copper-based enzymes.
Interactions may occur by simultaneous targeting of receptors, directly or indirectly. For example, both Zolpidem and alcohol affect GABAA receptors,
and their simultaneous consumption results in the overstimulation of
the receptor, which can lead to loss of consciousness. When two drugs
affect each other, it is a drug–drug interaction (DDI). The risk of a DDI increases with the number of drugs used.
A large share of elderly
people regularly use five or more medications or supplements, with a
significant risk of side-effects from drug–drug interactions.
Drug interactions can be of three kinds:
additive (the result is simply the expected effect of each drug taken independently),
synergistic (combining the drugs leads to a larger effect than expected), or
antagonistic (combining the drugs leads to a smaller effect than expected).
It may be difficult to distinguish between synergistic or additive interactions, as individual effects of drugs may vary.
Pharmacodynamic interactions are the drug–drug interactions that occur at a biochemical
level and depend mainly on the biological processes of organisms. These
interactions occur due to action on the same targets; for example, the
same receptor or signaling pathway.
Effects
of the competitive inhibition of an agonist by increases in the
concentration of an antagonist. A drug's potency can be affected (the
response curve shifted to the right) by the presence of an antagonistic
interaction.
Pharmacodynamic interactions can occur on protein receptors. Two drugs can be considered to be homodynamic, if they act on the same receptor. Homodynamic effects include drugs that act as (1) pure agonists, if they bind to the main locus of the receptor, causing a similar effect to that of the main drug, (2) partial agonists if, on binding to a secondary site, they have the same effect as the main drug, but with a lower intensity and (3) antagonists, if they bind directly to the receptor's main locus but their effect is opposite to that of the main drug. These may be competitive antagonists, if they compete with the main drug to bind with the receptor. or uncompetitive antagonists, when the antagonist binds to the receptor irreversibly. The drugs can be considered heterodynamic competitors, if they act on distinct receptor with similar downstream pathways.
The interaction my also occur via signal transduction mechanisms. For example, low blood glucose leads to a release of catecholamines, triggering symptoms that hint the organism to take action, like consuming sugary foods. If a patient is on insulin, which reduces blood sugar, and also beta-blockers, the body is less able to cope with an insulin overdose.
Interactions based on pharmacokinetics
Pharmacokinetics is the field of research studying the chemical and biochemical factors that directly affect dosage and the half-life
of drugs in an organism, including absorption, transport, distribution,
metabolism and excretion. Compounds may affect any of those process,
ultimately interfering with the flux of drugs in the human body, increasing or reducing drug availability.
Based on absorption
Drugs that change intestinal motility may impact the level of other drugs taken. For example, prokinetic agents increase the intestinal motility, which may cause drugs to go through the digestive system too fast, reducing absorption.
The pharmacological modification of pH can affect other compounds. Drugs can be present in ionized or non-ionized forms depending on pKa, and neutral compounds are usually better absorbed by membranes. Medication like antacids can increase pH and inhibit the absorption of other drugs such as zalcitabine, tipranavir and amprenavir. The opposite is more common, with, for example, the antacid cimetidinestimulating the absorption of didanosine. Some resources describe that a gap of two to four hours between taking the two drugs is needed to avoid the interaction.
Factors such as food with high-fat content may also alter the solubility of drugs and impact its absorption. This is the case for oral anticoagulants and avocado. The formation of non-absorbable complexes may occur also via chelation, when cations can make certain drugs harder to absorb, for example between tetracycline or the fluoroquinolones and dairy products, due to the presence of calcium ions. Other drugs bind to proteins. Some drugs such as sucralfate bind to proteins, especially if they have a high bioavailability. For this reason its administration is contraindicated in enteral feeding.
Drugs also may affect each other by competing for transport proteins in plasma, such as albumin.
In these cases the drug that arrives first binds with the plasma
protein, leaving the other drug dissolved in the plasma, modifying its
expected concentration. The organism has mechanisms to counteract these
situations (by, for example, increasing plasma clearance),
and thus they are not usually clinically relevant. They may become
relevant if other problems are present, such as issues with drug
excretion.
Based on metabolism
Diagram of cytochrome P450 isoenzyme 2C9 with the haem group in the centre of the enzyme.
Many drug interactions are due to alterations in drug metabolism. Further, human drug-metabolizing enzymes are typically activated through the engagement of nuclear receptors. One notable system involved in metabolic drug interactions is the enzyme system comprising the cytochrome P450 oxidases.
CYP450
Cytochrome P450 is a very large family of haemoproteins (hemoproteins) that are characterized by their enzymatic activity and their role in the metabolism of a large number of drugs. Of the various families that are present in humans, the most
interesting in this respect are the 1, 2 and 3, and the most important
enzymes are CYP1A2, CYP2C9, CYP2C19, CYP2D6, CYP2E1 and CYP3A4. The majority of the enzymes are also involved in the metabolism of endogenous substances, such as steroids or sex hormones,
which is also important should there be interference with these
substances. The function of the enzymes can either be stimulated (enzyme induction) or inhibited (enzyme inhibition).
Through enzymatic inhibition and induction
If a drug is metabolized by a CYP450 enzyme and drug B
blocks the activity of these enzymes, it can lead to pharmacokinetic
alterations. A. This alteration results in drug A remaining in the
bloodstream for an extended duration, and eventually increase in
concentration.
In some instances, the inhibition may reduce the
therapeutic effect, if instead the metabolites of the drug is
responsible for the effect.
Compounds that increase the efficiency of the enzymes, on
the other hand, may have the opposite effect and increase the rate of
metabolism.
Oligonucleotide therapeutics
Unlike small-molecule drugs, approved RNAi-based therapeutics such as siRNA drugs do not significantly induce or inhibit cytochrome P450 (CYP) enzymes, and therefore require distinct frameworks for evaluating drug–drug interactions (DDIs).
Several interaction mechanisms relevant to oligonucleotide drugs have been identified:
Transporter competition: Many GalNAc-conjugated siRNA drugs (e.g., inclisiran, givosiran, lumasiran) are taken up by hepatocytes via the asialoglycoprotein receptor
(ASGPR). Co-administration of agents that saturate or alter this
receptor pathway may affect hepatic delivery of the siRNA payload.
Carrier protein binding: Some
oligonucleotide drugs bind serum albumin or lipoproteins. Competition
with highly protein-bound small molecules could alter free-drug
concentrations.
Indirect CYP modulation: siRNA drugs that silence transcription factors controlling CYP gene expression (e.g., silencing of PCSK9 influences LXR/SREBP pathways) may indirectly alter CYP expression in co-treated patients.
On-target miRNA network perturbation: Because endogenous microRNA
(miRNA) regulates the expression of drug-metabolizing enzymes and
transporters, therapeutic oligonucleotides that modulate miRNA activity
can produce secondary DDIs via altered enzyme expression rather than
direct enzyme binding.
Regulatory guidance from the FDA
recommends that sponsors of oligonucleotide drug applications assess
DDI potential through in vitro transporter studies and, where indirect
CYP modulation is plausible, through induction assays, even when direct
CYP inhibition is absent.
Examples of metabolism-based interactions
An example of this is shown in the following table for the CYP1A2 enzyme, showing the substrates (drugs metabolized by this enzyme) and some inductors and inhibitors of its activity:
Drugs tightly bound to proteins (i.e. not in the free fraction) are not available for renal excretion. Filtration depends on a number of factors including the pH of the urine. Drug interactions may affect those points.
With herbal medicines
Herb-drug interactions are drug interactions that occur between herbal medicines and conventional drugs. These types of interactions may be more common than drug-drug
interactions because herbal medicines often contain multiple
pharmacologically active ingredients, while conventional drugs typically
contain only one. Some such interactions are clinically significant, although most herbal remedies are not associated with drug interactions causing serious consequences. Most catalogued herb-drug interactions are moderate in severity. The most commonly implicated conventional drugs in herb-drug interactions are warfarin, insulin, aspirin, digoxin, and ticlopidine, due to their narrow therapeutic indices. The most commonly implicated herbs involved in such interactions are those containing St. John's Wort, magnesium, calcium, iron, or ginkgo.
Examples
Examples of herb-drug interactions include, but are not limited to:
Concomitant Ephedra and caffeine use has been reported to, in rare cases, cause fatalities.
Mechanisms
The mechanisms underlying most herb-drug interactions are not fully understood. Interactions between herbal medicines and anticancer drugs typically involve enzymes that metabolize cytochrome P450. For example, St. John's Wort has been shown to induce CYP3A4 and P-glycoprotein in vitro and in vivo.
Underlying factors
The factors or conditions that predispose the appearance of interactions include factors such as old age. This is where human physiology changing with age may affect the
interaction of drugs. For example, liver metabolism, kidney function,
nerve transmission, or the functioning of bone marrow all decrease with
age. In addition, in old age, there is a sensory decrease that increases
the chances of errors being made in the administration of drugs. The elderly are also more vulnerable to polypharmacy, and the more drugs a patient takes, the higher is the chance of an interaction.
Genetic factors may also affect the enzymes and receptors, thus altering the possibilities of interactions.
Patients with hepatic or renal diseases already may have difficulties metabolizing and excreting drugs, which may exacerbate the effect of interactions.
Some drugs present an intrinsic increased risk for a harmful interaction, including drugs with a narrow therapeutic index, where the difference between the effective dose and the toxic dose is small. The drug digoxin is an example of this type of drug.
Risks are also increased when the drug presents a steep dose-response curve, and small changes in the dosage produce large changes in the drug's concentration in the blood plasma.
Epidemiology
As of 2008, among adults in the United States of America older than 56, 4% were taking medication and/ or supplements that put them at risk of a major drug interaction. Potential drug-drug interactions have increased over time and are more common in the less-educated elderly even after controlling for age, sex, place of residence, and comorbidity.
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