ADMET (Absorption, Distribution, Metabolism, Excretion and Toxicity)

ADMET (Absorption, Distribution, Metabolism, Excretion and Toxicity) analysis was used to assess the pharmacokinetic properties and safety of the compounds. This analysis helps predict how PJ34 and its derivatives will behave in a living organism. A favorable ADMET profile demonstrates that the compounds have the potential to be developed as effective drugs. The parameters analyzed are the ability of the compound to be absorbed by the organism, how the compound is distributed in the tissues, how the compound is metabolized in the body, the efficiency with which the compound is eliminated and the potential adverse effects.

The ADMETlab 3.0 software was used to generate the ADMET reports for each compound. This tool uses QSAR (Quantitative Structure-Activity Relationship) computational models to relate chemical compounds to their biological characteristics. In this way, it is possible to analyze the absorption, distribution, metabolism, excretion, and toxicity characteristics of each compound, in addition to other important data, such as physicochemical properties. (XIONG et al., 2021)

The ProTox-3.0 software was used to evaluate the LD50 of the compounds and to deepen the toxicity data. Thus, it is possible to obtain a more complete overview of the possible side effects of the samples, which may make clinical tests unfeasible. (BANERJEE et al., 2024) (BANERJEE et al., 2018)

Physicochemical properties

1. Log S

   Log S, or logarithm of water solubility, is a parameter of the physicochemical properties of drugs. A high Log S value is expected because it connects to greater solubility in aqueous media, which facilitates gastrointestinal absorption and bioavailability of the compound (ADMETlab 3.0 Explanation, 2023).

2. Log P

   Log P is the logarithm of the partition between octanol and water and is an indicator of the lipophilicity of a compound. This parameter should be moderate; very high values affect water solubility and generate difficulties in gastrointestinal absorption. Despite the harmful effects of high values, very low values can lead to an inability to cross biological membranes, which should also be avoided (Alves et al., 2019). Therefore, a data in the range 1 and 3 is expected for this indicator.

3. Log D7.4

   Log D7.4 is a measure of the distribution of a compound between two phases at pH 7.4 and provides guidance on how the drug will behave in the human physiological environment. This parameter has specific limits; extreme values may compromise absorption and therapeutic efficacy (ADMETlab 3.0 Explanation, 2023). Therefore, the ideal value is between 1 and 3.

   
   

Medicinal chemistry

1. QED

   QED ( Quantitative Estimate of Drug-likeness ) is a metric that tells whether the general properties of chemical compounds in terms of " drug-likeness " are adequate. A high QED value shows that the compound has adequate solubility, chemical stability and a balanced lipophilic profile (Alves et al., 2019).

2. SAscore

   SAscore is another indicator of the feasibility assessment of a compound for pharmaceutical development. It is best with a low value, below a score of 6. This refers to the drug's ability to be absorbed and metabolized in the body. A low SAscore can represent obstacles in bioabsorption, which can restrict its therapeutic efficiency and increase the risk of failures during the clinical phases of development. (ADMETlab 3.0 Explanation, 2023)

   
   

Absorption

1. Caco-2 Permeability

   Permeability in cell models such as Caco-2 predicts intestinal absorption and bioavailability of a drug. Classified as good when high, this measurement indicates that compounds with good permeability have a greater chance of being absorbed after oral administration. The Caco-2 model simulates the intestinal barrier, which generates an assessment of the drug's ability to cross this barrier (ADMETlab 3.0 Explanation, 2023).

2. MDCK Permeability

   Like Caco-2 permeability, permeability analysis in MDCK (Madin-Darby Canine Kidney) cells is important to predict renal and intestinal absorption of drugs. Also classified as better when values are high, this parameter leads to compounds with a good ability to cross cell membranes; relevant for bioavailability (ADMETlab 3.0 Explanation, 2023).

3. Human Intestinal Absorption

   Human intestinal absorption refers to the ability of a drug to be absorbed by the gastrointestinal tract. This is considered better with a lower value (ADMETlab 3.0 Explanation, 2023).

Distribution

1. Plasma Protein Binding

   Plasma protein binding is part of the pharmacokinetics of drugs and is considered more favorable when low. The compound has a higher free fraction in plasma when binding is lower, which can be advantageous. However, too little binding can increase the risk of toxicity if the drug is not rapidly eliminated (ADMETlab 3.0 Explanation, 2023).

2. Volume of distribution

   The volume of distribution (Vd) is a parameter considered more appropriate in pharmacology when high. A high Vd shows that the drug is widely distributed throughout the body's tissues, which leads to good penetration into the desired target sites. In this way, the drug reaches effective concentrations in various biological compartments (ADMETlab 3.0 Explanation, 2023).

   
   

Metabolism

1. Likelihood of being a CYP1A2 inhibitor

   The probability of a compound being an inhibitor of the CYP1A2 enzyme is better when it is low. This is because inhibitors of this enzyme can interfere with the metabolism of other drugs, which can cause undesirable interactions that can restrict the efficacy and safety of concomitant treatments (ADMETlab 3.0 Explanation, 2023). Therefore, a low probability of inhibition is sought to minimize these risks.

2. Human Liver Microsomal Stability

   Human hepatic microsomal stability is more favorable at low values. If this value is reduced, the compound is rapidly metabolized by the liver. This factor defines part of the drug's viability over time; a slight degradation can result in a short half-life and frequent management requirements (ADMETlab 3.0 Explanation, 2023). Understanding this stability is essential to anticipate the drug's performance in the body.

   
   

Excretion

1. Plasma clearance

   Plasma clearance numerically represents the body's efficiency in eliminating substances, both exogenous and endogenous. A high clearance rate is desirable because it reduces the risk of toxic accumulation in the body, which is insurmountable in prolonged administration regimens. This parameter quantifies the body's ability to remove the drug from circulation by studying drug interactions that may affect elimination (ADMETlab 3.0 Explanation, 2023).

2. Half life

   The half-life of a compound is an indicator of the duration of its action in the body and is considered more favorable when it is high. A long half-life causes the drug to remain active in the plasma for longer before being eliminated. This reduces fluctuations in plasma concentrations, which reduces the risk of underdosage or overdose and enhances therapeutic efficiency (ADMETlab 3.0 Explanation, 2023).

   
   

Toxicity

1. Neurotoxicity

   Low neurotoxicity values are desirable in drugs intended for clinical use, since damage to the nervous system can seriously and irreversibly impact the health of patients. Neurotoxicity analysis in pharmaceutical development ensures that compounds do not pose unacceptable risks to the neurological health of treated individuals. (ADMETlab 3.0 Explanation, 2023).

2. Genotoxicity

   The genotoxicity of a drug is also ideally low. Concern about the risks related to genetic alteration is essential in studies that are aware of the pharmacological threats of introducing new compounds. The analytical rigor of genotoxicity preserves the genetic material of patients. (ADMETlab 3.0 Explanation, 2023).

3. DILI

   DILI ( Drug-Induced Liver Injury ) is ideally low. This parameter concerns the risk of compounds causing liver injury. DILI is a major cause of clinical development failures due to liver toxicity. A low incidence of DILI increases confidence among researchers and regulators about the safety of the proposed drug. This composition helps in communicating potential risks to healthcare professionals involved in patient care (ADMETlab 3.0 Explanation, 2023).

4. Carcinogenicity

   Carcinogenicity is another undeniably important parameter in the assessment of pharmacological viability. This indicator indicates the greater or lesser probability of a drug inducing cancer during its clinical use. Thus, by controlling the carcinogenicity value, harm to patients' health over time is eliminated (ADMETlab 3.0 Explanation, 2023).

5. Nephrotoxicity

   This value refers to the probability of renal damage in the clinical use of drugs. This parameter is part of the overall safety of newly developed drugs; renal damage can lead to severe complications and limit future therapeutic options. Low nephrotoxicity helps direct pharmacological research towards promising candidates without excessive concerns about adverse renal effects during the advanced phases of treatment (ADMETlab 3.0 Explanation, 2023).

6. A549 Cytotoxicity

   Cytotoxicity is the numerical representation of the chance of a drug causing damage to lung cells during its clinical use. This parameter is extremely important since prolonged exposure or overdose of these compounds in specific respiratory or pulmonary environments. Reduced cytotoxicity in A549 cells brings with it greater applicability of drugs to respiratory or pulmonary conditions. This increases the chances of these compounds being used efficiently without negatively impacting the health of patients treated for chronic respiratory or pulmonary diseases (ADMETlab 3.0 Explanation, 2023).

7. Respiratory toxin

   This concerns the chance of these compounds causing toxicity in the human respiratory tract. This parameter also relates to the overall safety of drugs developed specifically to treat respiratory or pulmonary conditions where prolonged exposures may occur. Low respiratory toxicity assures developers that their compounds are less likely to cause serious reactions in the upper or lower airways during prolonged or repeated clinical use. This aids in the clinical acceptance of these drugs by healthcare professionals involved in the treatment of respiratory conditions in treated patients (ADMETlab 3.0 Explanation, 2023).

8. FDAMDD

   A low FDAMDD value is also expected in drugs, as it is a parameter that reflects concerns about their general adequacy within the regulatory guidelines established by the FDA for newly developed drugs. This studies factors related to the safety and efficacy of proposed compounds before final approval by the competent regulatory agency; therefore, its analysis ensures adequate regulatory compliance throughout this complex process (ADMETlab 3.0 Explanation, 2023).

9. LD50

   The LD50 represents the median lethal dose at which 50% of patients die after exposure to the compound. (BANERJEE et al., 2024) (BANERJEE et al., 2018)

ADMETlab 3.0 Explanation. Scbdd.com . Available at:

< https://admetlab3.scbdd.com/explanation/#/med?id=sascore >. Accessed on: October 17, 2024.

BANERJEE, Priyanka et al. ProTox 3.0: a webserver for the prediction of toxicity of chemicals. Nucleic Acids Research , p. gkae303, 2024. Available at: < https://academic.oup.com/nar/article/52/W1/W513/7655780?login=false >. Accessed on December 28, 2024.

BANERJEE, Priyanka et al. ProTox-II: a webserver for the prediction of toxicity of chemicals. Nucleic acids research , vol. 46, no. W1, p. W257-W263, 2018. Available at: < https://academic.oup.com/nar/article/46/W1/W257/4990033?login=false >. Accessed on 28 December. 2024.

XIONG, Guoli et al. ADMETlab 2.0: an integrated online platform for accurate and

comprehensive predictions of ADMET properties. Nucleic acids research, vol. 49, n. W1, p. W5-

W14, 2021. Available at: < https://academic.oup.com/nar/article/49/W1/W5/6249611?login=false >. Accessed on: September 18, 2024.