Exploration of New Inhibitors as Anti-Alzheimer Agents Through Molecular Modeling ^†

Abstract

Alzheimer’s disease (AD) is a neurodegenerative disease that accounts for more than 80% of dementia cases worldwide. This a neurological disorder that encompasses various stages of development (mild, moderate, or severe cognitive impairment), including certain psychological and behavioral syndromes such as depression, psychosis, and aggression. The main drug classes currently used to treat AD are acetylcholinesterase (AChE) and butyrylcholinesterase (BChE) inhibitors. Advancements in bioinformatics and chemometrics have positioned the in silico approach as a pivotal tool in identifying novel therapeutic compounds.Therefore, we conducted a study to evaluate the effects of various newly developed N-substituted 5-chloro-2(3H)-benzoxazolone derivatives on AchE. The aim of this research paper was to utilize in silico ADMET profiling to investigate the potential of natural analogs as inhibitors of AchE, using computational techniques such as swissadme. Analysis of selected ligands with the highest affinity for the target was performed to evaluate ADME properties. The calculation of ADME properties proved that these ligands follow the rules of Lipinski, Veber, and Egan and confirmed the docking results, indicating that they are probably the best inhibitors. Furthermore, they could be utilized to create novel pharmaceutical medicines with which to treat individuals with AD.

1. Introduction

Alzheimer’s disease (AD), the major form of dementia, is a progressive neurodegenerative disease [1]. The disease manifests itself as numerous cognitive deficits, such as memory loss, cognitive impairment, difficulty thinking, and language impairment. The pathophysiology of this disease is not fully understood. Most approved medications can only treat the disease by alleviating its symptoms. The disease is accompanied by impaired cholinergic neurotransmission in the basal forebrain [2], leading to reduced cholinergic signaling. This impairment can be corrected with acetylcholinesterase inhibitors. Inhibition of acetylcholine (AChE) is a well-established therapeutic strategy that increases acetylcholine levels in the brain, thereby improving cognitive and memory function. This increase in AChE levels potentially improves cognitive function in individuals with AD. AChE is a key enzyme primarily found in cholinergic brain synapses and neuromuscular junctions.

For a candidate compound to become a drug, it must demonstrate appropriate pharmacokinetics, good pharmacological activity, and a low toxicity profile. It is also beneficial for molecules subjected to advanced bioactivity testing to demonstrate high bioavailability in addition to good activity. This ensures that only compounds with high potential and acceptable pharmacokinetic properties are selected for drug development [3].

In the context of Alzheimer’s disease, pharmacokinetic properties were predicted using computational methods. This study examines a series of 2-hydroxy-N-phenylbenzamide derivatives as potential multitarget ligands for Alzheimer’s disease. Compounds selected from the docking results were further evaluated for their physicochemical properties and ADMET characteristics. ADMET is a key element in drug development, in which drug interactions with the body are assessed. A successful drug candidate should not only be effective against the therapeutic target but also exhibit appropriate ADMET properties at a therapeutic dose.

2. Materials and Methods

Many potential therapeutic agents are not subject to clinical trials due to their absorption, distribution, adverse metabolism, and elimination (ADME) parameters; moreover, they do not allow for verification of drug compatibility. Our study was based on the analysis of the properties of relevant pharmaceutical products. In particular, Lipinski’s rule of five [4], Veber’s rule [5], Egan’s rule [6], surface polarity (TPSA), BBB permeability [7], and gastrointestinal absorption [8] were calculated using the online property calculation tool SwissADME (http://www.swissadme.ch/, accessed on 30 September 2014) [9] by importing the chemical structure and then the SMILES format.

3. Results and Discussion

Based on the results obtained from molecular docking [10]. A computational study of three selected ligands with the highest affinity for the target (Figure 1) was carried out to evaluate the properties of ADME, and the results are shown in Table 1.

Figure 1. Two- and three-dimensional representations of the best posed interactions of the complexes using molecular docking simulation: 4EY7-L18, 4EY7-L17, and 4EY7-L6.

Table 1. ADME properties for the three best AChE ligands.

	Physicochemical Properties					Lipophilicity		Pharmacokinetics		Druglikeness
	TPSA Å2	MW g/mol	Num. Rotatable Bonds	Num. H-Bond Acceptors	Num. H-Bond Donors	MLOGP	WLOGP	GI Absorption	BBB Permeant	Lipinski	Ghose	Veber	Egan
	AChE
L18	49.33	351.01	3	2	2	4.48	5.07	High	Yes	Yes; 1 violation	Yes	Yes	Yes
L17	49.33	316.57	3	2	2	3.97	4.41	High	Yes	Yes; 0 violation	Yes	Yes	Yes
L6	49.33	351.01	3	2	2	4.48	5.07	High	Yes	Yes; 1 violation	Yes	Yes	Yes

Lipophilicity is an important factor in the processes of solubility, absorption, distribution, metabolism, and excretion, as well as pharmacological activity. Hansch et al. [11] showed that highly lipophilic molecules are distributed and conserved within the lipid layers of cell membranes. For good oral bioavailability and optimal results, the log P must be 0 < log P < 3. When log P is too high, the drug has low solubility, and when log P is too low, the drug struggles to penetrate lipid membranes [12]. In the obtained results, all the ligands L17,L18, and L6 have values between 3.97 and log P 4.60. They possess positive log P values, which indicates that these ligands are very lipophilic but with low solubility and poor gastric tolerance [13].

According to the literature [14], in molecules, a surface area value (TPSA) of less than 140 Ų is a good predictor of oral bioavailability and ensures better transport across biological membranes. However, if the surface area (TPSA) is greater than 140, poor transport through the membrane occurs (incomplete oral absorption). According to the values given in Table 1, it can be noted that all ligands have TPSA values = 49.33 Ų, which means that they support excellent absorption and brain penetration of CNS drugs. The number of rotating bonds is also a topological parameter and a measure of molecular flexibility (threshold 10). Oral bioavailability requires that these ligands, upon binding to a protein, change their conformation only slightly. This corresponds to the results in Table [15]. HBAs in large numbers lead to low permeability through a bilayer membrane. A smaller number leads to better permeability. From the results of Table 1, it can be observed that all ligands have hydrogen acceptor numbers of less than 10 (O, N) and hydrogen donor numbers of less than 5 (OH, NH). Lipophilicity and the number of hydrogen bond donors appear to be key properties, as they have remained essentially constant in oral drugs over time [16]. In addition, the selected ligands have molecular weight values of less than than 500 Da, so they can pass through cell membranes easily and have a high level of gastrointestinal absorption, which contributes to good oral bioavailability.

Furthermore, it can be observed that compound L17 has a zero violation number, and the other compounds (L18, L6) have a violation number equal to 1 for the Lipinski rule. This shows that all molecules tested align with the rules of Lipinski, Ghose, Veber, and Egan.

4. Conclusions

Based on these results, we can confirm that these compounds do not cause any oral bioavailability problems and exhibit good properties compared to the target drugs (native ligands). They can probably be used as active oral drugs in the treatment of this disease.