Investigating QSAR models for Chemical Warfare Agents:

Biological, Biochemical, and Environmental Perspectives

EVA TAFAKI, MICHAIL CHALARIS

School of Chemistry,

Democritus University of Thrace,

St. Loukas, Kavala GR-65404,

GREECE

Abstract: - Quantitative Structure-Activity Relationship (QSAR) models are essential in predicting the

characteristics of chemical warfare agents (CWAs), offering crucial insights into their biological, biochemical,

and environmental activities. This paper examines how QSAR models elucidate the complex relationships

between molecular structures and CWA actions. By leveraging principles from biology, biochemistry, and

environmental research, QSAR models accurately predict key features such as CWA toxicity, reactivity, and

environmental persistence. This study explores the fundamental mechanisms behind CWA interactions with

biological systems, molecular targets, and environmental compartments, highlighting the potential of QSAR

models to guide the development of novel antidotes, decontamination strategies, and environmental monitoring

protocols. Integrating insights from various disciplines, this work underscores the significance of QSAR

modeling in enhancing our understanding of CWA properties and supporting informed decision-making in

defense, public health, and environmental management.

Key-Words: - Chemical warfare agents, A-Series, nerve agents, Novichok, Biology, Biochemistry,

Environmental Systems, QSAR models, toxicity.

Received: January 23, 2024. Revised: July 23, 2024. Accepted: August 24, 2024. Published: September 27, 2024.

1 Introduction

According to the Organization for the Prohibition of

Chemical Weapons (OPCW), chemical weapons are

chemical substances used to intentionally cause

death or harm through various toxic properties.

Examples of chemical weapons are ammunition and

various devices and equipment specially designed

and equipped with toxic chemicals. Chemical

weapons are divided into different categories of

agents such as choking agents, blistering agents,

hematological agents, neurological agents and riot

control agents.

The category of chemical weapons that will be

extensively studied is the neurotoxic agents that

block the enzyme acetylcholinesterase (AChE) in

the nervous system. This causes neurotransmitter

buildup between nerve cells or at synapses, resulting

in overstimulation of muscles, glands, and other

neurons. Neurotoxic substances are highly toxic and

have immediate effects, primarily through

absorption through the skin and lungs.

Agents of the G series and agents of the V

series, named for military purposes, are the two

primary classes of neurotoxic agents. Some G

agents, particularly tabun and sarin, are only present

in the environment for a short time. Other agents,

such as soman and cyclosarin, last longer and are

more dangerous to the skin. V agents are incredibly

potent, requiring only milligrams to kill, and they

can survive in the environment for extended periods.

Tabun (GA), Sarin (GB), Soman (GD), Cyclosarin

(GF), and the VX agent are examples of such

chemicals. These agents cause overstimulation of

the sympathetic nervous system, causing symptoms

in the peripheral and central nervous systems such

as tears, salivation, perspiration, impaired vision,

headache, difficulty breathing, and vomiting.

Neurotoxic chemicals cause seizures, loss of bodily

control, muscle paralysis (including the heart and

diaphragm), and loss of consciousness at larger

doses.

The V- and G-series agents were initially

utilized to create A- A-series compounds, with

claims of synthesizing and testing over a hundred

analogs. In the case of A-agents, the typical nerve

agent alkoxy substituent (- OR) on the central

phosphorus atom is replaced with a nitrogen

substituent. Substance-84, also known as A-230, is a

sarin derivative with an acetamidine moiety in place

of the O- isopropyl group. [1], it's noteworthy that

the majority of A-series agents use the A-230

design. A-232 and A-234 structures are

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acetamidine-containing methoxy and ethoxy analogs

of A-230. Other analogs are guanidine analogs, such

as A-242 and A-262. A- 230 and A-242 are

phosphonates, whereas A-232, A-234, and A-262

are phosphates. A-234 can be synthesized from

direct binary precursors in the same way that V- and

G-series agents are. The A-series constructions are

presented in Table 1 (Appendix), [1], [2], [3], [4].

1.1 The Importance of Understanding the

Toxicity behind A- Series

The toxicity of chemical warfare agents is important

due to several reasons such as the immediate impact

on everyone who is exposed and further

implications for public health and safety. These

substances possess a high degree of toxicity and can

induce rapid and severe health repercussions.

Chemical warfare agents, crafted for military

applications, primarily serve strategic purposes.

Public health and safety precautions are of

paramount importance, given the substantial threats

posed by accidental releases or intentional

deployment in warfare or acts of terrorism.

These chemicals specifically, attack the enzyme

acetylcholinesterase (AChe) which is used in the

transmission of ongoing neuro signals, including

acetylcholine, which is excitatory neurotransmitter.

As a result, a nerve impulse will be slower than the

chatochin decay rate, and ultimately the nervous

system will be impaired. Correspondingly, the

patient exhibits dyspnea, fitting, debility, or even

death in severe instances. As a result, we observe

the impairment of the respiratory system as well as

the musculoskeletal system, and other organ

systems are affected. It is essential to have an in-

depth knowledge of the impact of certain agents on

the environment, including the substances that are

long-term pollutants that endanger both water and

soil as resources. On the other hand, the modern

medicine has pinpointed pills of atropine and

pralidoxime that can reduce the degree of the effect.

This field of research calls for further investigation

to validate it.

1.2 The Importance of QSAR Modeling in

Estimating A- Series Properties

When assessing the environmental or human health

effects of these compounds, QSAR modeling can to

a certain extent remedy the apparent lack of data.

Thus, in the present study physico– chemical

properties of nerve agents have been estimated

using QSAR models. It should be emphasized that

the environmental processes of these substances are

no different from other substances. However, for

environmental studies, the extreme toxicity of the

nerve agents obviously must be considered.

QSAR modeling is beneficial when it comes to

predicting the properties of these substances as there

is no need for laboratory work or experiments, thus,

there is no human exposure. Moreover, QSAR

models provide the advantage of high speed in

predictions, allowing the research to identify the

substance, view the structure, and predict the

biological activity, the toxicity, and lethality of the

substance.

2 Model Assessment and QSAR

Fundamentals

Toxicity, biological activity, and physicochemical

properties are some of the parameters that are most

often predicted using QSARs (Quantitative

Structure-Activity Relationships), which are

particularly relevant when gathering experimental

data is difficult or very expensive. Actual measures

like REACH, which requires the registration of all

chemicals with production of more than one tonne

and assesses their environmental influences and

health, show the need for QSAR modeling. Other

than that, it is realized that QSAR models are a

better alternative for high-cost experimental data,

[5], [6].

2.1 Statistical Methods

The development of quantitative structure-activity

relationship (QSAR) models can be achieved using

statistical approaches. These methods span

numerous models, starting with simple and linear

models, and advance to complex non-linear models

which are designed to increase confidence in the

data. These methods will be reviewed about model

creation and use.

2.2 Modern Nonlinear Methods

Various machine learning technologies have been

employed for pharmaceutical data analysis, covering

a diverse range of approaches. These methods, often

integrating the simpler techniques mentioned earlier,

can generate nonlinear models with increased

prediction accuracy. In the following section, we

will present a concise overview of some frequently

utilized techniques in the pharmaceutical industry.

The Randοm Fοrest approach [7] is a modern

machine learning algοrithm that has become the

industry standard for developing comprehensive

QSAR mοdels. [8], a Randοm Fοrest mοdel is made

up of a large number (usually 100-500) οf individual

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decision or regression trees created using a process

known as bagging.

Fig. 1: A decision tree fοr predicting blοοd brain

barrier permeation CNSp+ represents lοg PS

measurement οf>−2 and CNSp – represents a lοg PS

measurement of < -3; alοg P is the Ghοse-Crippen

partitiοn cοefficient; fpSA3 is the fraction pοlar

surface area; #RοtBοnds is the number of rοtatable

bοnds; and #Acceptοrs is the number οf hydrοgen

bοnd acceptοrs

As shown in Figure 1, each tree in the fοrest is

cοnstructed using a different bοotstrap sample of the

training data, where a boοtstrap sample cοnsists οf

N compounds chosen with replacement for the

οriginal dataset. By examining οnly a pοrtiοn οf the

descriptοrs fοr each tree nοde split, a secοnd

element οf randοmization is intrοduced. These two

sοurces οf randοmness ensure that each tree

represents the input data uniquely, and thus

averaging predictiοns acrοss the fοrest prοvides

cοnsistently accurate results. Furthermοre, Randοm

Fοrests give sοlid methοds fοr assessing the relative

relevance οf input descriptοrs, and the variance οf

predictions acrοss trees prοvides accurate estimates

οf expected prediction errors. The random Forest

package in R can be used to create random forest

models. The cForest machine learning approach, a

variant οf the Randοm Fοrest machine learning

methοd, allοws fοr the cοnditional relevance οf

input descriptοrs to be assessed.

The performance οf a mοdel is οften evaluated

using bοth graphical representation and various

statistical measurements. In this context, QSAR

models can be divided into two types:

(1) regression models, which provide quantitative

predictions of the modeled property, and (2)

classification models, which provide predictions in

the form of class labels, such as active or inactive.

Charts displaying the correlation between

predictions and measured values for either the

external test set or cross-validated predictions are

used to analyze regression models. The strength of

the correlation, the range of input and predicted

data, the existence of outliers, and the even

distribution of predictions across the value range

should all be considered while analyzing correlation

charts. Detecting clusters around specific values

may indicate that the mοdel is detecting simple

patterns, such as distinguishing separate subseries

within the data with varying activity levels.

3 Clinical Implications for Human

Health

The exposure to organophosphate compounds leads

to distinct clinical effects, typically manifesting in

three stages in humans. [9], initially, there is an

acute cholinergic phase, occurring shortly after

exposure and lasting around 12 to 24 hours. This

phase encompasses various symptoms, such as

muscarinic, nicοtinic, and central nervοus system

symptoms. Muscarinic symptoms invοlve chest

tightness, increased secretiοns, cοughing, nausea,

vomiting, abdominal cramps, diarrhea, sweating,

salivation, tearing, blurred vision, and incontinence.

Nicotinic symptoms may include muscle spasms

and weakness. Furthermore, the central nervous

system is affected, resulting in emotional instability,

dizziness, sleep disturbances, nightmares, headache,

confusion, stupor, speech difficulties, seizures,

coma, and potentially fatal outcomes in severe

cases.

The second stage involves the intermediate

syndrome (IS), [10]. IS appears 1-4 days after the

acute cholinergic phase and before the onset of

delayed polyneuropathy. It is characterized by

severe weakness of the proximal muscles of the

limbs and cranial nerve disorders. Difficulty in

breathing can progress to respiratory failure

following paralysis of the diaphragm and other

respiratory muscles. Complete recovery occurs

within 4-

21 days with appropriate care. Although the

exact pathogenesis of the intermediate syndrome is

currently unknown, there may be alterations in the

function and activity of nicotinic receptors at the

neuromuscular junction, [11]. IS has not been

described in cases of poisoning by neurologic

agents; however, there is a connection with muscle

changes observed after poisoning by tabun, soman,

and sarin in experimental animals, [12]. Following

organophosphate insecticide poisoning in humans, it

has been reported that 10- 30% of patients may

develop IS, [13], [14].

The third and final stage involves delayed

polyneuropathy and typically manifests 7-14 days

after exposure to the organophosphate compound. It

usually results in symmetric weakness of the

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peripheral muscles in the hands and feet with

varying degrees of sensory impairment. Currently,

phosphorylation of another enzyme, esterase, a

target of organophosphate-induced neuropathy

(OPIDN), is believed to be responsible for the

dysfunction. [15], [16], unlike the intermediate

syndrome, it is highly unlikely for neurotoxic agents

to have the capability to induce polyneuropathy,

possibly due to the low concentrations of

neurotransmitters required to affect

acetylcholinesterase compared to the high

concentrations needed to inhibit NTE. Studies have

shown that only a small percentage of NTE

inhibition from the brain and spinal cord of hens

undergoes aging.

3.1 Other Effects of Organophosphate

Compounds

Studies involving both humans and animals have

documented a range of disorders affecting various

functional systems following exposure to

organophosphate compounds, [17].

3.1.1 Effects on the Central Nervous System

Exposure to organophosphate compounds can lead

to intricate changes in mental functioning, [18]

including diminished memory and alertness,

reduced information processing speed, and

psychomotor abilities. Additionally, symptoms like

depression, anxiety, and irritability may manifest.

These effects are particularly concerning in wartime

situations, as they could significantly impair

soldiers' combat effectiveness. Studies suggest that

the long-term consequences of cognitive impairment

may persist for up to a year, whether from a single

exposure or chronic exposure to low-level nerve

agents or pesticides. [19], furthermore, individuals

may experience subsequent behavioral and

psychological changes, [20], [21].

In an industrial accident, 40 civilians were

accidentally exposed to GB vapors, [22]. This did

not result in significant changes in the

cholinesterase of red blood cells (RBC) in those

exposed. However, there was a temporary

incapacity among the exposed. Individuals reported

symptoms such as weakness, headaches, sensations

of heat-cold, dizziness, nightmares, feeling warmth

or increased sweating, drowsiness, insomnia,

irritability, tremors, sweating, facial spasms,

anorexia, diarrhea, and pseudo-sensory edema.

Other studies on individuals with neurological

factors have revealed symptoms and signs such as

frontal headaches, occipital pain, eye vessel dilation,

rhinorrhea, nausea, vomiting, chest tightness, and

blurred vision. These are similar to those observed

after exposure to insecticides. Fatigue, lethargy, and

poor or no sleep were observed in some who were

exposed, while skin exposure caused sweating for

periods of up to 34 days. Cognitive dysfunctions,

which may be particularly relevant for military

effectiveness, include disturbances in three-

dimensional spatial coordination and judgment.

In animals, after exposure to the agents, initial

changes observed include edema, astrocytic, and

peri-vascular hemorrhages. Neuronal degeneration

and occasionally diffuse necrosis may be observed

along with more discrete infarctions. These changes

may be particularly detected in the hippocampus

and the cerebellar cortex, [23].

3.1.2 Genotoxic and Carcinogenic Effects

The genetic toxicity and carcinogenic effects are

worrisome because of the irreversible nature of the

disease mechanisms and the extended latent period

before they become apparent. Certain scholars [24],

[25] propose that these agents possess the capability

to undergo alkylation. Nonetheless, in comparison

to chemical substances, the reaction rate of these

agents with enzymes like AChE and

phosphorylation is significantly higher.

3.1.3 Mutation

The hazardous effects of mutagenesis will rely on

the capability of these agents to cause observable

genetic damage to DNA, encompassing mutations,

deletions, displacements, and chromosomal

abnormalities. Both the pesticides malathion and

dimethoate have induced sister chromatid exchanges

in human cells and chromosomal aberrations in

human lymphocytes. Likewise, Dichlorvos, an

insecticide containing organophosphate compounds,

has also been associated with mutagenic

abnormalities, [26], [27].

3.1.4 Teratogenesis

Teratogenesis is defined as the induction of

dysplasia in living offspring without a decrease in

the number of births. Embryonic defects did not

arise after continuous administration of agents in

animals, except at doses significantly affecting the

health of the mother. Many agents are teratogenic in

bird and fish embryos. The mechanism of

teratogenesis in birds may involve the inhibition of

an enzyme, cyanoformamidase [28], which does not

appear to be significant for humans.

3.1.5 Pregnancy

In experimental animals, exposure to

organophosphate compounds during pregnancy

induces prenatal and postnatal death and congenital

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abnormalities, including spinal deformities, limb

defects, polydactyly, intestinal hernia, cleft palate,

and hydronephrosis. [29], damage to organs related

to male fertility, such as the testes, has been

reported following exposure to these agents. [30],

[31], in humans, intoxication during the third month

of pregnancy results in miscarriage as continuing

the pregnancy is deemed hazardous, [32].

3.1.6 Immune System

Epidemiological studies have indicated that these

agents may impact the human immune system. [33],

[34], compounds like parathion can suppress

lymphocytes and chemical immunity, following

doses that produce cholinergic effects. Significant

impairment of protective white blood cell

(neutrophil) function and increased upper

respiratory tract infection frequency have been

observed in workers occupationally exposed to

pesticides. Reduction in both serum cholinesterase

and RBC activity has also been noted, [35].

3.1.7 Metabolic Function

Several metabolic (e.g., glucose metabolism) [36]

and endocrine activity (adrenal and thyroid

hormones) disorders have been reported in animals

and humans following exposure to organophosphate

substances. [37], in evaluating the health impacts of

nerve agent exposure, it is essential to investigate

the presence of such disorders.

4 Environmental Impacts of

Neurological Agents

4.1 Effects on Soil Environment

The environmental repercussions of neurological

agents are significant, particularly concerning the

soil ecosystem. Soil chemical properties frequently

suffer degradation due to military actions aimed at

harming individuals and infrastructure, or disrupting

agricultural activities, along with the cessation of

military training exercises. This often results in

large-scale population movements to safer regions

amidst armed conflicts. However, the influx of

people into these areas often exacerbates

environmental challenges due to the potential

overuse of natural resources. This can lead to severe

ecological disruptions, including extensive

deforestation, desertification, unsustainable

exploitation of groundwater, and contamination of

both soil and groundwater. These adverse effects are

commonly observed near densely populated refugee

camps and migration routes across international

borders.

The expected outcome of neurological agents on

soil involves the eradication of specific organisms

residing in the area. However, there is a lack of

studies aiming to confirm this impact, as noted in

the available literature. One prominent neurological

agent widely utilized, called VX, presents as a clear,

amber-colored, odorless, oily liquid that can

dissolve in water and poses severe toxicity even at

minimal exposure levels. Unlike other neurological

agents such as tabun (GA), sarin (GB), and sοman

(GD), VX exhibits notably lower atmospheric

pressure and persists in the soil environment due to

its strong absorption properties. [38], once absorbed

into soil colloids, its toxicity diminishes

significantly. [39], research on VX-induced soil

contamination has observed near-cοmplete

degradatiοn οf the pοllutant within three weeks,

regardless of sοil type. However, intact VX was still

detectable in soil samples stored at 4°C for over a

year post-contamination. [40], evapοration is

succeeded by hydrolysis, serving as the primary

mechanism for the lοss οf neurοlοgical agents frοm

sοil. Sarin can permeate through the soil in gaseous

fοrm under hοt, arid conditions, weighing about five

times that οf air. Its hydrοlysis οccurs thrοugh the

lοss οf fluοrine, followed by a slower lοss οf the

alkοxy grοup. Hydrοlysis rates depend on sοil

temperature and pH, with resultant prοducts

typically being nοn-tοxic. Sοman, while having

lοwer atmοspheric pressure and vοlatility cοmpared

tο sarin, undergοes a similar hydrοlysis prοcess.

Hοwever, sοman's decοmpοsition prοducts,

generally nοn-tοxic, are mοre water- sοluble and

have less affinity fοr οrganic matter than sarin

decοmpοsition products, [41].

Many microbial species can break down

organophosphorus compounds in soil,

demonstrating their effectiveness in the colonization

and restoration of contaminated soils. The

phοsphοtriesterase (PTE) frοm sοil bacteria, such as

Pseudοmοnas diminuta, is invοlved in deactivating a

broad range of neurological organophosphorus

agents. [42], recent studies have led to significant

advancements in the catalytic activities of

recognized PTE variants, with improvements up to

15,000 times compared to the wild-type enzyme

[43], supporting a combined strategy οf rational

design and directed evοlution as a pοtent tοοl fοr

discοvering increasingly effective enzymes fοr the

detοxification οf οrganοphοsphοrus neurοlοgical

agents.

Neurological agents persist in pοοrly drained

sοils, where anaerοbic conditions prevail. [44], sοil

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recοvery in such cοnditions can be achieved thrοugh

injectiοns οf evapοrated hydrοgen perοxide. [45],

[46], mοst degradation prοducts are less tοxic than

the parent cοmpοunds, but VX, HN-2, L, and ED

fοrm tοxic intermediates that are more resilient than

the parent cοmpοunds. [47], organοphοsphοrus

agents are essentially cοnverted intο lοw-sοlubility

phοsphοric salts, resulting in a net gain fοr the

mineralοgical aggregation οf the sοil. Accοrding tο

UN Resοlution 687, the prοduction and stοrage οf

neurοlοgical agents were οutlawed by the Chemical

Weapοns Cοnventiοn οf 1993.

4.2 Impact on the Marine Ecosystem

4.2.1 Regulatory Aspects of Chemical Weapon

Disposal at Sea

Certain international organizations have addressed

the issue of chemical munitiοns being discarded at

sea. The quantity οf weapοns dispοsed, the lοcatiοns

(bοth actual and dοcumented), and the potential

impacts οn humans and marine ecοsystems have

been evaluated, bοth thrοugh cοnducting new

primary research and assimilating existing available

data. [48], [49], the chemical agents remaining in

dispοsed munitiοns pose two main threats:

environmental risk assοciated with the chrοnic οr

acute release οf agents from their casings into the

subsea environment, and the risk of human health

assοciated with human expοsure tο agents leaching

οntο land οr οtherwise surfacing. [50], traditiοnal

rates οf dissοlution and hydrοlysis οf an agent

serves as useful indicatοrs οf its ecοlogical tοxicity

and indirect threat to humans. Agents highly sοluble

in water dissοlve rapidly and are expected to

disperse quickly in seawater due to the vast vοlume

of the οcean. Agents undergoing rapid dissοlution

and hydrοlysis shοuld thus lead to lοwer lοng-term

tοxicity than envirοnmentally resistant agents.

Phοsgene, chlοrοacetοphenοne, and blοοd agents

have dissοlutiοn and hydrοlysis rates that make

them unlikely to chronically threaten underwater

ecοsystems. LD50 or LCt50 values may be unknown

or may οnly cοme frοm animal mοdels.

4.2.2 Neurological Agents

Tabun dissolves in seawater and breaks down within

a few days, with cyanide being the only toxic

byproduct of its degradation. Sarin, being colorless

and odorless, remains a liquid at 10°C. It does not

mix with water and rapidly breaks down (within a

few days) into hydrofluoric acid and isopropyl

methylphosphonic acid. Both resulting compounds

from the hydrolysis process degrade quickly in

water, hence they are considered relatively safe

within the oceanic environment. Soman, more

lipophilic than tabun and sarin, decomposes slowly

into pinacolyl methylphosphonic acid and

methylphosphonic acid. These breakdown products

also exhibit minimal toxicity. [51], soman is the

only G-agent expected to possess some

environmental persistence. [52], VX demonstrates

an uncommon characteristic of increased water

solubility at lower temperatures. [53], with its slow

hydrolysis rate, VX is anticipated to have a subsea

half-life of 5.4 years. The initial hydrolysis products

retain toxicity and acetylcholinesterase activity,

thereby prolonging potential adverse effects on

marine ecosystems. Predicting post-release

concentrations is challenging as they depend on

local oceanic disturbances and currents. Neurotoxic

agents typically undergo eventual hydrolysis in

seawater, forming non-toxic degradation products.

4.2.3 Impact on Fish from Chemical Weapons

Triphenylarsine, adamsite, and sulfur mustard are

expected to exhibit chronic toxicity in fish. This

may be related to the hydrophobic nature of sulfur

mustard and its arsenic oil components, as they are

expected to persist in the environment much longer

than other factors. [54], the relative resilience of the

sea may also contribute to the persistence of sulfur

mustard lumps and continuous exposure of

fishermen. Of these compounds, fish and tissue

modeling predicted that only adamsite would be

present in fish muscles: adamsite concentrations in

cod and haddock were predicted to be 0.485 mg/kg

and 0.167 mg/kg, respectively. These levels were

considered too low to cause health impacts from fish

consumption, although a separate model predicted

an oral RfD for adamsite to be 0.00003 mg/kg body

weight/day. Several mass marine "deaths," including

starfish, benthic fish, and dolphins, were initially

attributed to chemical weapons, but the causation

has either not been proven or definitively attributed

to another cause. To date, mass marine deaths have

not been confirmed to be caused by chemical

weapons disposed of at sea. Predicting the risk to

humans from consuming fish exposed to underwater

chemical agents is challenging. Scenario modeling

for water concentration and bioaccumulation data in

combination with oral RfD has suggested a risk.

Triphenylarsine appears to be the chemical agent

posing the greatest threat to humans consuming

seafood, followed by sulfur mustard and adamsite.

[55], the potential toxicity of triphenylarsine arises

from its higher bioaccumulation rate. In MEDEA's

assessment of disposal in the Arctic seas, arsenic in

seafood from discarded chemical weapons was

estimated to pose moderate risk to indigenous

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populations repeatedly consuming seafood from the

same collection areas throughout their lives.

4.2.4 Impact on Marine Microorganisms from

Chemical Weapons

It has been demonstrated that chemical agents in

landfills affect local marine organisms. Of particular

interest are bacterial species resistant to arsenic,

sulfur mustard, and the breakdown products of

sulfur mustard, thus participating in the degradation

of arsenic, sulfur mustard, and thiodiglycol.

Basidiomycota fungal species are found in marine

environments and are capable of breaking down

sulfur mustard, but they are not regularly assessed

during landfill research cited in the literature.

Arthrobacter, Achromobacter, and Pseudomonas

species resistant to thiodiglycol were found to be

functional in the breakdown of thiodiglycol at

relevant seawater temperatures (280 K). In two

landfills, one in the Bornholm Basin and one off the

Norwegian coast, it was found that 20-90% of

heterotrophic organisms were resistant to sulfur

mustard. Up to 58% of bacteria were resistant to

sulfur mustard breakdown products, with dominant

species being Pseudomonas and Bacillus. Sampling

studies in Baltic and Skagerrak disposal areas

showed that 20% to 98% of bottom- dwelling

heterotrophs are resistant to sulfur mustard

breakdown products. The increase in the

microbiome resistant to sulfur mustard breakdown

products may also have mitigating effects on

pollutants, as toxic agents would degrade and be

removed from the environment more rapidly.

However, in cases where contamination of

harvested seafood has occurred, such seafood has

been preemptively destroyed, [56], [57].

5 Results of QSAR Model

Development for the A SERIES

5.1 Finite Dose Skin Permeation (FDSP)

Calculator

The finite dose skin permeation calculator facilitates

the computation of the skin permeation coefficient

(Kp). [58], numerous models have been devised to

ascertain steady-state permeation from an aqueous

solution of limitless volume, yet these models do

not align with typical workplace exposure scenarios.

However, when a dose, regardless of its size, is

administered to partially or fully hydrated skin, this

program determines fluxes, concentrations in the

skin, and absorbed amounts. Specifically, the

software computes the skin penetration coefficient

and absorption of chemicals concerning evaporation

following the application of a test substance to the

skin. The skin permeability coefficient (Kp) serves

as a predictor for chemical skin penetration.

Although many mathematical models rely on Kp

data, conflicting Kp values have been observed,

prompting concerns about the overall reliability of

these measurements. Kp is measured in units of (cm

h-1). To ensure the effectiveness of the finite dose

skin permeation calculation and obtain the desired

outcome, it is essential to input specific parameters.

These include the chemical name and type of the

substance under testing, LogKow, melting and

boiling points, molecular weight, vapor pressure,

permeability, and information regarding double or

triple bonds and the presence of a ring. The

hydrophilic/lipophilic property of a compound is

determined by the octanol-water partition

coefficient (Kow). Initially applied in drug and

pesticide discovery and design, Kow has become a

critical factor for any chemical, significantly

influencing its behavior within a living organism

and in the environment. The results of the program

in relation to the VP, Kp, Jmax and Tmax of the A-

series are presented in Table 2 and percentages of

systemic absorption, evaporation, stratu corneum,

Molacular Weight and log Kow are presented in

Table 3, respectively.

The toxicity data presented above are based on

oral administration. The skin is the most likely route

of absorption. A review of the International Journal

of Molecular Science yielded data on vapor

pressures, melting and boiling points, and octanol-

water partitioning coefficients for the 12 compounds

investigated. Table 3 contains the estimated vapor

pressures for the chemicals examined. It should be

observed that very low vapor pressures were

detected for the A-230, A- 232, A-234, A-038, A-

039, A-042, and especially for the A- 242, but

slightly higher vapor pressures appear to prevail for

the compounds A-036, A-040, A-041, and A-037,

respectively. For probable absorption through the

skin, the vapor pressure, as well as structural

properties such as the presence of

hydrophilic/hydrophobic groups, will be assessed.

The skin permeation data were then computed using

the Finite Dose Skin Permeation calculator, and the

results are shown in Table 3. The skin permeation

(Kp) of A-230 was determined to be 3.952E-5

cm/hr, while the maximal flux, Jmax, was

determined to be 0.029 mg/ cm2hr.

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Table 2. Calculated vapor pressure, skin permeation,

and maximum absorptive flux. Tmax corresponds to

the time to maximum systemic absorption

Compound

VP mm

Hg

Kp cm/hr

Jmax

μg/cm2hr

Tmax

hr

A-230

0,01598

3,952*10-5

0,029

3,081

A-232

0,0111

1,862*10-5

0,038

2,85

A-242

0,01275

3,397*10-5

0,021

1,855

A-035

0,00434

3,876*10-5

0,00348

25,022

A-036

0,13875

2,282*10-4

0,003678

5,476

A-037

0,5535

8,553*10-4

0,002008

6,785

A-038

2,28

3,290*10-3

0,001575

7,964

A-039

0,01148

1,821*10-5

0,004598

13,282

A-040

0,0528

9,545*10-5

0,005173

3,378

A-041

0,2055

3,572*10-4

0,002979

3,609

A-042

0,825

1,356*10-3

0,001803

2,85

Table 3. The percentage distribution of systemic

absorbed, evaporated, and sorbed to the stratum

corneum. Further, the molecular weight (MW) and

the octanol-water partitioning coefficient are given

Compound

Systemic

Absorbed

pct.

Evaporation

pct.

Stratu

Corneum

pct.

MW

g/mol

A-230

12,13

95,03

0,06

194,19

A-232

15,78

89,31

0,08

210,19

A-234

8,02

109,07

0,01

224,21

A-242

15,34

90,00

0,13

239,27

A-035

2,25

166,49

0,02

209,93

A-036

1,42

286,10

0,01

193,47

A-037

1,11

618,57

0,01

177,02

A-038

8,86

101,75

0,08

240,03

A-039

3,31

134,17

0,02

223,96

A-040

1,83

199,20

0,01

207,50

A-041

1,26

375,51

0,01

191,05

A-042

13,51

92,75

0,13

254,05

It should be emphasized that these statistics are

subject to some uncertainty because skin permeation

is highly dependent on where the skin is taken from

the human body. Several intriguing features arise

from the data reported in Table 5. Several intriguing

features arise from the data reported in Table 5. To

begin, the skin permeation value, Kp, of Novichoks

A-042, A-038, and A-232 is much lower than that of

A-037 and A-041. Second, significant changes in

the percentage of the chemical that is absorbed

systemically should be noticed. Thus, the absorbed

percentage for compounds A-232 and A-242 is

approximately 15 times that of compounds A-037

and A-041. Concurrently, a large increase in the

proportion of compound evaporated is seen, which

is perfectly consistent with the fluctuation in vapor

pressure. Third, all substances have a relatively low

percentage of the stratum corneum and, as a result,

always reach the plasma. Fourth, the variance in

time to maximal flux is highlighted. When exposed

to one of these substances, this lag time may be

significant. It should be noted that these figures are

for healthy skin. Possible skin damage may reduce

the lag-time dramatically. Because Novichoks have

a low molecular volume in general, the proceding

observations cannot be explained only by a

molecular size.

5.2 Prediction of Activity Spectra for

Biologically Active Substances (PASS)

The PASS program can compute the characteristics

of biologically active compounds. Specifically, it

enables the computation of over 300

pharmacological properties and biological

mechanisms using the substance’s structure as a

basis. The outcomes from these calculations are

presented in a tabular format, indicating the

activities of the studied properties ( Activity) and

providing specific values that determine whether a

compound is active (Pa) or inactive (Pi) concerning

the relevant property, [59].

• If Pa>0.7 the compound is likely to show the

same activity at the experimental level, but there

is a possibility that the compound is analogous

to a known pharmaceutical substance.

• If 0.5<Pa<0.7 the compound is likely to show

the same activity at the experimental level, but

with a lower probability, and there is no

possibility that the compound is analogous to a

known drug substance.

• If Pa<0.5 the compound is not likely to show

the same activity at the experimental level.

Yet, should this behavior be identified during

the experimental phase, it suggests that the

substance under consideration might constitute a

novel chemical compound. The PASS platform

scrutinized a total of eight activities related to

Novichok compounds.

5.2.1 Cholinergic

In the parasympathetic system, specific sensory

nerves known as cholinergic receptors are evident.

The term "cholinergic" is derived from the presence

of the neurotransmitter acetylcholine, which serves

as the principal neurotransmitter in the

parasympathetic system. Cholinergic

neurotransmitters fall into two classes, distinguished

by the compound that stimulates them in each

case—nicotine and muscarinic. [60], [61], various

substances can impact the activity of these

neurotransmitters, either by stimulating, enhancing,

or imitating the neurotransmitter acetylcholine. This

phenomenon is referred to as cholinergic toxicity.

Organophosphate and carbamate compounds

primarily account for substances responsible for

cholinergic toxicity. Depending on the specific

acetylcholine neurotransmitter affected, cholinergic

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toxicity can manifest distinct symptoms in the

human body. An excess of acetylcholine in

muscarinic neurotransmitters results in increased

secretions (sweat, tears, saliva, stomach fluids),

bronchi constriction, decreased heart rate, and

abdominal cramps. Similarly, in nicotine

neurotransmitters, an excess of acetylcholine can

induce muscle spasms or even paralysis due to

overstimulation of the nerves transmitting messages

to the muscles. [62], [63], the results of the program

for the cholinergic activity are presented in Table 4.

5.2.2 Toxicity

Toxicity refers to a substance's capacity to induce

harmful side effects on a single cell, a group of

cells, an organ system, or the entire body. While all

chemicals can cause some degree of harm, a

chemical is deemed toxic when even a small amount

can be detrimental to a living organism. Conversely,

if a large quantity of the chemical is necessary to

cause harm, it is considered relatively non-toxic.

The toxicity of a substance hinges on three crucial

factors: its chemical structure, the extent of

absorption by the body, and the organism's ability to

detoxify and eliminate the substance. However,

when comparing the toxicity of two compounds,

their structure is the sole essential factor. This is

because the absorption and detoxification

capabilities can vary not only between different

species but also among organisms of the same

species. [64], the results of the program for the toxic

activity are presented in Table 6.

5.2.3 Neurotoxicity

Neurotoxicity pertains to a substance's ability to

induce adverse effects in the central nervous system,

peripheral nerves, or sensory organs. A chemical is

classified as neurotoxic if it can instigate a

consistent pattern of neural dysfunction or bring

about changes in the chemistry or structure of the

nervous system. [65], neurotoxicity can manifest at

any stage in the life cycle, from gestation through

senescence, and its symptoms may vary with age.

The nervous system appears particularly susceptible

to damage during its developmental stages, and the

consequences of early injuries may become apparent

only as the nervous system matures and ages. [66],

the results of the program for the neurotoxic activity

are presented in Table 5.

5.2.4 Respiratory Failure

The respiratory system plays a crucial role in

supplying the body with oxygen and expelling

carbon dioxide. Any failure in performing these

tasks can result in respiratory failure. [67],

Novichoks, similar to other organophosphate

compounds, induce the phosphorylation of serine

hydroxyl residues on the acetylcholine esterase

enzyme upon entering the human body. This

modification to the enzyme leads to an

accumulation of acetylcholine, a neurotransmitter

essential in cholinergic signaling pathways. The

heightened levels of acetylcholine cause

dysregulation in the cholinergic system, manifesting

in both central and peripheral clinical symptoms.

Given the potential for detrimental physiological

effects, it is imperative to comprehend the intricate

mechanisms underlying the biochemical changes

generated by Novichoks.

Respiratory failure is one of the most serious

cholinergic effects of organophosphate poisoning,

and it is mostly caused by central processes.

Specifically, the neural fibers that function with

glutaminergic and muscarinic neurotransmission

form the pre-Bötzinger afferent complex, a region in

the posterior medulla. Excessive production of the

substance acetylcholine in this area can suppress

breathing, resulting in respiratory failure. The

results of the program for the respiratory failure are

presented in Table 7.

5.2.5 Multiple Organ Failure

The mechanisms underlying the multiorgan failure

syndrome remain poorly understood, suggesting that

multiple biological pathways may be involved in the

early stages of the disease. In critically ill patients,

functional abnormalities may be the main cause of

organ failure, rather than anatomical defects. Likely,

a mechanism of a defensive or reactive nature -

rather than simple failure - is the main process at

play in this context. This theory states that a

decrease in oxidative phosphorylation and

mitochondrial activity sets off the loss of organ

function, which in turn causes a decrease in cellular

metabolism. This effect on mitochondria may be

related to acute phase changes in inflammatory

mediators and hormones. The results of the

program for the multiple organ failure activity are

presented in Table 8.

5.2.6 Hematotoxic

The hematotoxic effects induced by chemical

substances can be broadly categorized into two

primary groups: (i) alterations in the number of

circulating blood cells and cell types, and (ii)

modifications to the oxygen-carrying capacity of

hemoglobin. Anemia and leukopenia characterize

conditions where the numbers of red and white

blood cells per unit volume of blood decrease, while

polycythemia and leukemia denote conditions

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marked by an increase in the numbers of red and

white blood cells. Disorders such as

methemoglobinemia and carboxyhemoglobinemia

are associated with a diminished capacity of red

blood cells to transport oxygen.

Methemoglobinemia stems from the oxidation of

ferrous iron in hemoglobin to the ferric state, while

carboxyhemoglobinemia arises from the

complexation of carbon monoxide with hemoglobin.

The results of the program for the hematotoxic

activity are presented in Table 9.

5.2.7 Carcinogenic

Carcinogenic properties refer to a substance's

capacity to either induce or exacerbate cancer.

Carcinogens can cause genetic alterations or

interfere with regular cell processes, which can

result in unchecked cell division. If you are exposed

to certain compounds at work, in the environment,

or through your lifestyle, there is a possibility that

cancer will develop. It is critical to recognize and

understand the properties of substances that have the

potential to cause cancer to safeguard public health.

The results of the program for the carcinogenic

activity are presented in Table 10.

5.2.8 Teratogen

Teratogens are chemicals that can cause congenital

abnormalities in a developing embryo or baby.

These are substances known for their ability to

worsen fetal abnormalities when treated or taken

during pregnancy. Among the teratogens are

pharmaceuticals, drugs, chemicals, certain diseases,

and poisonous substances. In addition, teratogen

exposure may increase the chance of stillbirth,

premature labor, and miscarriage. The results of the

program for the teratogenic activity are presented in

Table 11.

Warfare chemical agents are assessed for their

effects by detailed examination, taking into account

a variety of factors, such as their effects on

cholinergic, toxic, neurotoxic, respiratory, multiple

organ failure, haematotoxic, carcinogenic, and

teratogenic activities. For this assessment, PASS

software, an advanced tool providing a

comprehensive understanding of the

pharmacological properties and biological

mechanisms of action of the different chemical

agents, is used. The PASS platform evaluates more

than 300 attributes according to the agents'

structural features. The outcomes are then tabulated

and the activity levels of these attributes are

classified as either active (Pa) or inactive (Pi).

Table 4. PASS results for the cholinergic activity

Compound

Pa

Pi

Activity

A-230

0,205

0,023

Cholinergic

A-232

0,198

0,025

Cholinergic

A-234

0,2

0,025

Cholinergic

A-242

0,179

0,033

Cholinergic

A-262

0,173

0,036

Cholinergic

Novichok 5

0,123

0,077

Cholinergic

Novichok 7

0,15

0,049

Cholinergic

A-038

0,198

0,025

Cholinergic

A-039

0,206

0,023

Cholinergic

A-040

0,302

0,011

Cholinergic

A-041

0,319

0,01

Cholinergic

A-042

0,242

0,016

Cholinergic

A-043

0,113

0,088

Cholinergic

A-044

0,147

0,052

Cholinergic

A-045

0,129

0,07

Cholinergic

Unknown 1

n/a

Cholinergic

Unknown 2

n/a

Cholinergic

Unknown 3

0,2

0,025

Cholinergic

Iranian

Novichok

0,137

0,062

Cholinergic

A-230

0,113

0,088

Cholinergic

A-232

0,147

0,052

Cholinergic

A-234

0,129

0,07

Cholinergic

Table 5. PASS results for the neurotoxic activity

Compound

Pa

Pi

Activity

A-230

0,662

0,034

Neurotoxic

A-232

0,64

0,037

Neurotoxic

A-234

0,695

0,03

Neurotoxic

A-242

0,745

0,024

Neurotoxic

A-262

0,726

0,026

Neurotoxic

Novichok 5

0,685

0,031

Neurotoxic

Novichok 7

0,746

0,023

Neurotoxic

A-038

0,727

0,025

Neurotoxic

A-039

0,842

0,013

Neurotoxic

A-040

0,881

0,008

Neurotoxic

A-041

0,877

0,008

Neurotoxic

A-042

0,842

0,013

Neurotoxic

A-043

0,847

0,012

Neurotoxic

A-044

0,898

0,005

Neurotoxic

A-045

0,932

0,004

Neurotoxic

Unknown 1

0,893

0,006

Neurotoxic

Unknown 2

0,56

0,052

Neurotoxic

Unknown 3

0,623

0,04

Neurotoxic

Iranian

Novichok

0,748

0,023

Neurotoxic

A-230

0,847

0,012

Neurotoxic

A-232

0,898

0,005

Neurotoxic

A-234

0,932

0,004

Neurotoxic

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Table 6. PASS results for the toxic activity.

Compound

Pa

Pi

Activity

A-230

0,566

0,067

Toxic

A-232

0,558

0,069

Toxic

A-234

0,548

0,068

Toxic

A-242

0,612

0,059

Toxic

A-262

0,604

0,061

Toxic

Novichok 5

0,526

0,075

Toxic

Novichok 7

0,585

0,064

Toxic

A-038

0,606

0,06

Toxic

A-039

0,744

0,037

Toxic

A-040

0,808

0,026

Toxic

A-041

0,798

0,028

Toxic

A-042

0,731

0,039

Toxic

A-043

0,872

0,015

Toxic

A-044

0,895

0,012

Toxic

A-045

0,899

0,012

Toxic

Unknown 1

0,882

0,014

Toxic

Unknown 2

0,538

0,073

Toxic

Unknown 3

0,522

0,075

Toxic

Iranian

Novichok

0,64

0,055

Toxic

A-230

0,872

0,015

Toxic

A-232

0,895

0,012

Toxic

A-234

0,899

0,012

Toxic

Table 7. PASS results for the respiratory failure

activity

Compound

Pa

Pi

Activity

A-230

0,663

0,034

Respiratory Failure

A-232

0,64

0,038

Respiratory Failure

A-234

0,705

0,028

Respiratory Failure

A-242

0,741

0,024

Respiratory Failure

A-262

0,723

0,026

Respiratory Failure

Novichok 5

0,708

0,028

Respiratory Failure

Novichok 7

0,759

0,021

Respiratory Failure

A-038

0,76

0,021

Respiratory Failure

A-039

0,849

0,012

Respiratory Failure

A-040

0,907

0,007

Respiratory Failure

A-041

0,903

0,008

Respiratory Failure

A-042

0,864

0,01

Respiratory Failure

A-043

0,824

0,014

Respiratory Failure

A-044

0,921

0,006

Respiratory Failure

A-045

0,762

0,021

Respiratory Failure

Unknown 1

0,684

0,031

Respiratory Failure

Unknown 2

0,461

0,079

Respiratory Failure

Unknown 3

0,646

0,037

Respiratory Failure

Iranian

Novichok

0,759

0,021

Respiratory Failure

A-230

0,824

0,014

Respiratory Failure

A-232

0,921

0,006

Respiratory Failure

A-234

0,762

0,021

Respiratory Failure

Table 8. PASS results for the multiple organ failure

activity

Compound

Pa

Pi

Activity

A-230

0,748

0,02

Multiple Organ Failure

A-232

0,683

0,035

Multiple Organ Failure

A-234

0,646

0,046

Multiple Organ Failure

A-242

0,779

0,014

Multiple Organ Failure

A-262

0,721

0,026

Multiple Organ Failure

Novichok 5

0,687

0,034

Multiple Organ Failure

Novichok 7

0,779

0,014

Multiple Organ Failure

A-038

0,329

0,205

Multiple Organ Failure

A-039

0,522

0,09

Multiple Organ Failure

A-040

0,565

0,073

Multiple Organ Failure

A-041

0,536

0,084

Multiple Organ Failure

A-042

0,302

0,229

Multiple Organ Failure

A-043

0,43

0,134

Multiple Organ Failure

A-044

0,398

0,153

Multiple Organ Failure

A-045

0,398

0,153

Multiple Organ Failure

Unknown 1

0,366

0,175

Multiple Organ Failure

Unknown 2

0,353

0,185

Multiple Organ Failure

Unknown 3

0,592

0,063

Multiple Organ Failure

Iranian Novichok

0,729

0,024

Multiple Organ Failure

A-230

0,43

0,134

Multiple Organ Failure

A-232

0,398

0,153

Multiple Organ Failure

A-234

0,398

0,153

Multiple Organ Failure

Table 9. PASS results for the carcinogenic activity

Compound

Pa

Pi

Activity

A-230

0,284

0,047

Carcinogenic

A-232

0,248

0,055

Carcinogenic

A-234

0,265

0,051

Carcinogenic

A-242

0,357

0,032

Carcinogenic

A-262

0,322

0,038

Carcinogenic

Novichok 5

0,411

0,026

Carcinogenic

Novichok 7

0,465

0,021

Carcinogenic

A-038

0,683

0,009

Carcinogenic

A-039

0,242

0,057

Carcinogenic

A-040

0,328

0,036

Carcinogenic

A-041

0,308

0,041

Carcinogenic

A-042

0,26

0,052

Carcinogenic

A-043

0,614

0,011

Carcinogenic

A-044

0,541

0,015

Carcinogenic

A-045

0,567

0,014

Carcinogenic

Unknown 1

0,664

0,009

Carcinogenic

Unknown 2

0,292

0,045

Carcinogenic

Unknown 3

0,14

0,125

Carcinogenic

Iranian

Novichok

0,155

0,107

Carcinogenic

A-230

0,614

0,011

Carcinogenic

A-232

0,541

0,015

Carcinogenic

A-234

0,567

0,014

Carcinogenic

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Table 11. PASS results for the Teratogen activity.

Compound

Pa

Pi

Activity

A-230

0,213

0,136

Teratogen

A-232

0,253

0,112

Teratogen

A-234

0,29

0,096

Teratogen

A-242

0,283

0,098

Teratogen

A-262

0,348

0,08

Teratogen

Novichok 5

0,36

0,076

Teratogen

Novichok 7

0,433

0,061

Teratogen

A-038

n/a

Teratogen

A-039

0,21

0,138

Teratogen

A-040

0,296

0,094

Teratogen

A-041

0,27

0,103

Teratogen

A-042

0,177

0,16

Teratogen

A-043

0,23

0,125

Teratogen

A-044

0,422

0,063

Teratogen

A-045

0,25

0,114

Teratogen

Unknown 1

0,879

0,006

Teratogen

Unknown 2

0,374

0,073

Teratogen

Unknown 3

n/a

Teratogen

Iranian

Novichok

0,252

0,113

Teratogen

A-230

0,23

0,125

Teratogen

A-232

0,422

0,063

Teratogen

A-234

0,25

0,114

Teratogen

5.3 ProTox-II

ProTox-II is an online toxicity lab that may be

accessed via a web server. It is intended to forecast

different toxicological consequences linked to a

given chemical structure. The platform forecasts the

potential toxicity of both real and virtual chemicals

using computer-based models trained on real data,

whether gathered from in vitro or in vivo research.

ProTox-II determines the acute toxicity class and

multiple endpoints for an input compound by

evaluating chemical similarities to known dangerous

compounds and applying trained machine learning

models.

The platform aims to position itself as a freely

available and comprehensive computational tool for

in silico toxicity prediction, catering to

toxicologists, regulatory agencies, computational

chemists, and medicinal chemists. The ProTox web

server utilizes both chemical similarity and the

identification of toxic fragments to accurately

predict toxicity. It introduces a distinctive feature

for predicting toxicity class through methods based

on both similarity and fragments, accompanied by

alerts indicating potential toxicity targets. An

important advantage of ProTox-II lies in its

adaptability for future enhancements. It incorporates

an oral toxicity model that relies on a predictive

method analyzing two-dimensional similarity to

compounds with known LD50 values and

identifying fragments overrepresented in toxic

substances. The validation method employs leave-

one-out cross-validation, calculating the three

nearest neighbors from the training set for each

compound using fingerprint similarity. Results for

the input compound's oral toxicity prediction are

presented as a predictive LD50 value (mg/kg), as

presented in Table 12.

Table 12. ProTox-II results for acute toxicity

(LD50) and the predicted toxicity class

Compound

Predicted

LD50 (mg/kg)

Predicted

Toxicity Class

A-230 Russian

280

3

A-232 Russian

1

A-234 Russian

100

3

A-242 Russian

1340

4

A-262 Russian

1

Novichok 5

1600

4

Novichok 7

3000

5

A-230

American

49

2

A-232

American

14

2

A-234

American

1017

4

A-035

14

2

A-036

14

2

A-037

2

1

A-038

1000

4

A-039

8

2

A-040

8

2

A-041

2

1

A-042

1000

4

A-043

49

2

A-044

14

2

A-045

1017

4

Unknown 1

150

3

Unknown 2

300

3

Unknown 3

14

2

Iranian

Novichok

233

3

Toxic doses are often given as LD50 values in

mg/kg body weight. The LD50 is the median lethal

dose meaning the dose at which 50% of test subjects

die upon exposure to a compound. Toxicity classes

are defined according to the globally harmonized

system of classification of labeling of chemicals

(GHS). LD50 values are given in [mg/kg].

5.3.1 Class I

Fatal if swallowed (LD50 ≤ 5): High-risk classes in

ProTox-II are the categories that can cause serious

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health consequences to humans if they are

ingested. The body can uptake of these compounds

which lead rapid onset of symptoms and even this

may be life-threatening. The LD50 value of ≤ 5

mg/kg is equivalent to extreme toxicity and exhibits

high potency to induce poisoning, even in low

doses.

5.3.2 Class II

Fatal if swallowed (5 < LD50 ≤ 50): Compounds in

this class are predicted to have LD50 values that

indicate a high level of acute toxicity. These

chemicals represent a major threat to human well-

being and the environment, with some adverse

reactions being reported even at fairly low

concentrations. Extremely poisonous substances

may cause rapid occurrence of symptoms, damage

to organs, and, ultimately, can lead to

fatality. Extreme examples of very toxic substances

include some pesticides, heavy metals, and a few

industrial chemicals.

5.3.3 Class III

Toxic if swallowed (50 < LD50 ≤ 300): Compounds

in this class have less acute toxicity than in class II.

However, exposure to substances in this class may

not have immediate effects, but prolonged exposure

may lead to serious effects on human health.

5.3.4 Class IV

Harmful if swallowed (300 < LD50 ≤ 2000): Those

substances calculated to produce mild acute toxicity

are predicted to have LD50 values reduced as

compared with class III, II and I. However,

exposure to harmful agents can physically be

harmful at higher doses or with constant

administration over time. These types of substances

could be industrial solvents, household chemical

agents and even some pharmaceuticals.

5.3.5 Class V

May be harmful if swallowed (2000 < LD50≤

5000): Compounds classified in class V are

predicted to cause irritation or inflammation upon

contact with skin, eyes, or mucous membranes,

rather than systemic toxicity. While irritants may

not pose significant acute health risks at typical

exposure levels, they can still cause discomfort,

allergic reactions, and skin sensitization in

susceptible individuals. Common examples of

irritants include certain cleaning agents, cosmetics,

and environmental pollutants.

5.3.6 Class VI

Non-toxic (LD50 > 5000): Compounds assigned to

this class are predicted to have LD50 values

indicating minimal acute toxicity. These substances

are unlikely to cause significant adverse effects even

at high doses and are considered safe for general

use. However, it's essential to note that even

substances classified as practically nontoxic may

still pose risks at very high concentrations or under

certain exposure scenarios. Examples of practically

nontoxic substances include many food additives,

some cosmetic ingredients, and certain

environmental contaminants at low concentrations.

6 Discussion

6.1 Finite Dose Skin Permeation (FDSP)

Calculator

After successfully running the finite dose skin

permeation calculator program we conclude that the

primary route of absorption is likely through the

skin. Data on vapor pressures, melting and boiling

points, and the octanol-water were collected,

revealing relatively low values for A-230, A- 232,

A-234, A-038, A-039, A-042, and especially A-242,

while somewhat higher vapor pressures are

observed for A- 036, A-040, A-041, and A-037.

Vapor pressure, coupled with structural features like

the presence of hydrophilic/hydrophobic groups,

plays a crucial role in potential skin absorption. Skin

permeation data were then estimated using the

Finite Dose Skin Permeation calculator, and the

results are summarized in Table 3. For A-230, the

skin permeation (Kp) value was determined to be

3.952E-5 cm/hr, with a maximum flux, Jmax, of

0.029 mg/cm2hr. It's important to note the

uncertainty in these data, given that skin permeation

appears to be influenced by the specific location on

the human body from which the skin is obtained.

The skin permeation value (Kp) for Novichoks

A-042, A-038, and A-232 is significantly lower than

those for A-037 and A-041. There are substantial

differences in the percentage of the compound

systemically absorbed, with A-232 and A-242

exhibiting absorption percentages approximately 15

times higher than A-037 and A-041. All compounds

display a markedly low percentage in the stratum

corneum, consistently reaching the plasma. Lastly,

there is a noteworthy variation in the time it takes to

reach maximum flux, emphasizing the potential

significance of this lag time when exposed to these

compounds. It must be emphasized that these data

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correspond to undamaged skin, and any skin

damage could significantly reduce the lag time.

Understanding the behavior of the chemical

during skin contact is as important as understanding

the mechanism of the skin absorption

process. Central considerations comprising vapor

pressures, melting and boiling points and octanol-

water partition coefficients determine the speed and

depth to which a chemical diffuses into the

skin. Vapor pressure, being the balance between the

vapor and the condensed phase, represents how

much a chemical will try to turn into the air. The

high vapor pressure enables the product to dissipate

rapidly from the skin surface, which may result in a

decrease in the absorption time. Additionally,

melting and boiling points define the temperature

ranges on which substances change from one phase

into another. A lower melting point translates to the

liquid state even at normal temperature making the

substance more disposed to skin contact while lower

boiling point may trigger rapid evaporation which

will eventually reduce skin absorption. The octanol-

water partition coefficient, indicating the solubility

of a substance in lipophilic (octanol) versus

hydrophilic (water) environments, exhibits the layer

passage across skin layers. Lipid rich stratum

corneum has a higher partition coefficient, and the

substances with a higher partition coefficient

penetrate through it and reach the deeper layers of

the epidermis. Together, understanding these

physicochemical properties brings new light about

chemicals and the skin, in turn, provides a basis for

the absorption kinetics and toxicological

implications of those chemicals

There are different skin penetration levels of the

A-series chemicals. These levels have profound

effects on the organism along several domains. In

this regard, products with higher penetration rates

pose the risk of systemic dissemination and

therefore, require detailed safety evaluations which

may result in tighter regulatory norms.

In addition, the formulation of topical products

depends much on an in-depth understanding of these

variations so that, a specialized formulation might

be needed to mitigate systemic absorption for potent

drugs associated with high penetration property

while at the same time assuring effective localized

therapy. On the one hand, compounds with

decreased permeation may need formulation

adjustments for the purpose of achieving an

adequate skin penetration potential for optimal

therapeutic outcomes. This is accompanied by

increased impact of the exposure risk management,

where higher penetration rate compounds imply

more exposure and hazards for both, handlers and

users, which in turn, requires robust risk reduction

measures for human health protection. Differences

in the skin permeation level also provide a

foundation for various regulatory decisions,

requiring more efforts on the penetration and

absorption if it is a novel or re-evaluated product.

However, those differences can also promote more

studies and the development of new delivery

systems and improved treatment efficacy as the

result of better probing of the intricacies of biology

and the physicochemical properties.

FDSP (Finite Dose Skin Permeation) calculators

provide important hints about the performance of

compounds on the skin and their absorbability into

the body. It is, however, mostly important their

misinterpretation by an observer should be taken

under consideration. Built-in assumptions and

simplifications can oversimplify the nature and

complexities of substance features and one's skin,

thereby continuously preventing the model from

giving expected or real data. Skin variability and

suboptimal experimental data contribute to the

difficulty in predicting the measure. The application

area becomes limited by uncertainties concerning

input parameters and calibration, thus preventing the

generalization of the findings to all types of

scenarios. A further concern is that such erratic

dynamics might defeat the very aims of the FDSP

calculators. Combining the experimental data,

factually mentioning uncertainties, and verifying the

hypotheses will be inevitable procedures for the

FDSP simulator to produce accurate and trustworthy

results.

Skin damage greatly affects the skin

permeability and the dermal lag time, which play a

critical element in the chemical absorption exams,

needed for an effective and accurate toxicological

evaluation. Through any type of skin damage such

as breakdown of the barrier function, the chemicals

penetrate deeper into the skin with higher absorption

rates. This means, on the one hand, damaged skin

would be much more permeable, allowing

compounds to penetrate the bloodstream faster and

deeper than in healthy skin. This thorough

permeability may completely remove the slack time

that can cause delays in risk assessments and

formulation decisions. FDSP calculators might

underestimate the breadth of consequences,

triggering modified safety policies and adjusted

experiment settings as a remedy. Skin damage

assessment sheds light on the safety requirements of

clinical and occupational environments and elevates

the level of risk assessment for human purposes.

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6.2 Prediction of Activity Spectra for

Biologically Active Substances (PASS)

The Prediction of Activity Spectra for Biologically

Active Substances (PASS) is a tool in the

cheminformatics computational model that enables

prediction of the biologically active substances.

PASS, in this case, examines the structural

similarities of a chemical to the database for various

activities and outcomes, so crucial for detecting

chemical weapons. Applying the structure-activity

relationship (SAR) principles, the task of predicting

activities at PASS will be based on the comparison

of structural properties to well-known patterns. The

very first step of this process is the input of

compound structure, followed by the search for the

important molecular components that can contribute

to biological activity. The similarities allow the

prediction of a formula which facilitates such

demands as pharmaceutical business and ecological

security programs, with chemical warfare detection

being key.

The structure-activity relationships (SAR)

principle that asserts that the chemical composition

of a compound governs what action it will carry in a

biological system is the key found in the model of

Prediction of Activity Spectra for Biologically

Active Substances (PASS). Research by analyzing

the rigid structure of the compound and, thus,

comparing it to database patterns, PASS ultimately

determines the possible biological activities by

probability, based on common motifs in the

structures. Think of such structural considerations as

functional groups and molecule properties

promoting size and solubility for a better

understanding of the chance establishments. PASS

identifies and classifies physicochemical properties

and binding modes/interactions with biological

targets to predict how molecules will behave based

on size, stereoisomerism, and solubility. Numbers

assigned imply molecular building block

resemblance with known active compounds of

different contexts, and thus activation predictions

become more accurate.

After successfully running the program Pass for

all 8 activities, we can discuss about the possibility

of the occurrence of each activity. For the

cholinergic activity, there is a higher chance of

occurring in substances A-040 and A-041 possibly

due to the F and Cl atoms. While there’s a lower

chance of occurring in substances A-043 and A-044.

For the neurotoxic activity, there is a 40% more

chance of occurring in A-045 and A-234 than in any

other substance. For the toxic activity, we can see

that substances A-040, A-043, A-044, A-045, A-

230, A-232, and A-234.

For the respiratory failure activity, it is observed

that the substances A-040, A-041, A-044, and A-

232 American have the highest probability of

inducing this activity, while the substances A-230,

A-232, and A-234 have the lowest. On the other

hand for the multiple organ failure activity we can

see that substances A-230, A-232, A-234, A-242,

and A-262 have the highest probabibility while A-

038, A-039, and A-040 have the lowest. For the

hematotoxic, carcinogenic and teratogen activities

all the substances have low probabilities of causing

these activities except for the A-045 and the A-232

American which have high chances of causing the

hematotoxic activity. Lastly, A-038 has a high

chance of causing carcinogenic activity and the

Unknown 1 substance has a high chance of causing

teratogenic activity, respectively.

While the Prediction of Activity Spectra for

Biologically Active Substances (PASS) tool offers

valuable insights into chemical compound activities,

it has limitations and uncertainties to consider.

Prediction accuracy heavily depends on the quality

and diversity of the reference database, potentially

skewing results towards certain compounds or

activities and limiting applicability, especially for

novel drugs. Even though PASS predictions produce

credible estimates for the activity likelihood, there

are no guarantees that this may be directly

observable. The biological processes are extremely

complex and systematic and the interactions

between compounds with the environment are non-

static. On the other hand, PASS's overly-dependence

on structural features enables it to overlook the

nuanced molecular interactions or face the variables

that may bother its accuracy such as target

specificity and cellular milieu. To verify the PASS

predictions one must use critical interpretation

uniting the computational chemistry studies,

biology, and experimental data in favor of correct

interpretations.

6.3 ProTox-II

ProTox-II is a computational tool that calculates the

toxicological effects of a certain chemical

compound, with the ability to detect if it is

hazardous to life or not. Median lethal dosage

(LD50) the laboratory test aiming at evaluating the

probability of being killed by 50% of the test

population is a very important parameter of

toxicology.

The numerical representation of LD50 values is

indispensable as it allows for a scientific basis for

acute toxicity. Toxicologists can evaluate the

relative toxicity of various compounds and develop

dose-response connections by calculating the LD50

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of a compound through experimental testing on

animal models. Greater toxicity is indicated by a

lower LD50 value, which suggests that less of the

substance is needed to cause harm. Predicted LD50

values are used in ProTox-II to group substances

into toxicity groups according to how likely they are

to cause acute toxicity. Generally speaking, these

toxicity groups span from extremely toxic to almost

harmless, with several intermediary categories

denoting different toxicity levels.

All substances were studied under the ProTox-II

program and the results were significant. Substances

A-232, A-262, A-037 and A-041 were found to have

the lowest median lethal dose (LD50) and thus,

categorized as the number 1 predicted toxicity class.

Substances A-230 American, A-232 American, A-

035, A-036, A-039, A-040, A-043, A-044, and the

Unknown 3 substance have a median lethal dose

from 5 to 50 mg/kg and thus categorized as class 2

of predicted toxicity. Substances A- 230, A-234,

Unknown 1, Unknown 2, and Iranian Novichok

have a median lethal dose from 50 to 300 mg/kg and

are categorized as class 3 of predicted toxicity.

Substances A-242, Novichok 5, A-234, A-038

American, A-042 American, and A- 045 American

have a median lethal dose from 300 to 2000 mg/kg

and are categorized as class 4 of predicted toxicity.

Lastly, the substance Novichok 7 has the lowest

lethal dose of 3000 mg/kg and is categorized as

class 5 of predicted toxicity.

While ProTox-II offers valuable insights into

chemical compound toxicological characteristics,

users must recognize its limitations and

uncertainties. Unlike computational models based

on structure-activity relationships (SAR), ProTox-II

predictions might not have a full representation of

the real biological systems and special compound

structures, which may result in inaccuracies,

especially for the compounds which is not in the

training set. Model accuracy depends on the quality

and diversity of the training set with new drugs

resulting in increased bias. The lack of training sets

data that is open to the public makes it even more

difficult to evaluate. Besides that, the toxicological

reactions disparity among species and individuals

claim a careful interpretation. Exploring both the

principles of Toxicology and Computational

Chemistry is therefore of great importance as it

plays a role in robustly evaluating ProTox-II

predictions, avoiding false conclusions without

experiment confirmation.

7 Conclusion

In conclusion, QSAR models like FDSP, PASS, and

ProTox-II are very useful for the toxicological

studies of chemical warfare agents, including those

from the A-series. Skin Permeation analysis by

Finite Dose Spread Spectrometer (FDSP) will also

reveal the significance of studying through the skin

as the main source of input to the test substances.

Vapor pressures, molecular structure parameters,

and skin permeability values, particularly those of

A-230, revealed certain absorption routes, which

highlights their significance of in the assessment of

skin porosity. Nevertheless, uncertainties do exist as

a result of unforeseeable displacements of skin

locations, which can influence the precision of the

predictions. The PASS software is found to help

provide critical information on how compounds may

act. Differentiation in the cholinergic, neurotoxic,

pulmonary, hematotoxic, carcinogenic, and

teratogenic actions of the drugs caused the

occurrence of various types of toxicological

profiles. The observation of how some drugs bring

out some behaviors shows how sophisticated their

toxicological effects are and promotes the

understanding of their biological interactions.

Moreover, the ProTox-II tool provides an in-depth

evaluation of the toxicological problems related to

the compounds by putting into different toxicity

categories the compounds according to the expected

toxicity. Certain substances like A-232 and A-262

are being classified in the highest predicted toxicity

level category, meaning a severe risk coming from

each one's exposure. In contrast, some compounds

demonstrate varying toxicity within the A-series, as

the compounds are classified on the toxicity scale

according to their average LD values. The findings

strengthen the knowledge we have on the possible

threats that are associated with each substance, and

hence, they serve as a guide for future studies and

inform risk mitigation efforts employed in defense

and environmental applications.

Acknowledgement:

We express our heartfelt gratitude to the GRID

Computing Center at the Democritus University of

Thrace (DUTh), Kavala Campus, Greece, for their

generous provision of the necessary CPU resources

crucial for the successful implementation of our

research.

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APPENDIX

Table 1. A-Series structure

Structure

Name

Citation

A-230

[2]

A-232

[2]

A-234

[2]

A-242

[2]

A-262

[2]

Novichok 5

[2]

Novichok 7

[2]

A-230

[3]

A-232

[3]

A-234

[3]

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DOI: 10.37394/23208.2024.21.29

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Volume 21, 2024

Structure

Name

Citation

A-035

[4]

A-036

[4]

A-037

[4]

A-038

[4]

A-039

[4]

A-040

[4]

A-041

[4]

A-042

[4]

A-043

[4]

A-044

[4]

Structure

Name

Citation

A-045

[4]

Unknown 1

[4]

Unknown 2

[4]

Unknown 3

[4]

Iranian

Novichok

[4]

Contribution of Individual Authors to the

Creation of a Scientific Article (Ghostwriting

Policy)

Michail Chalaris was responsible for the

supervision. The authors equally contributed to the

present research, at all stages from the formulation

of the problem to the final findings and solution.

Sources of Funding for Research Presented in a

Scientific Article or Scientific Article Itself

No funding was received for conducting this study.

Conflict of Interest

The authors have no conflicts of interest to declare.

Creative Commons Attribution License 4.0

(Attribution 4.0 International, CC BY 4.0)

This article is published under the terms of the

Creative Commons Attribution License 4.0

https://creativecommons.org/licenses/by/4.0/deed.en

_US

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DOI: 10.37394/23208.2024.21.29

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Volume 21, 2024