Development of non-peptide ACE inhibitors as novel and potent cardiovascular therapeutics: An in silico modelling approach

In silico study to recognize novel angiotensin-converting-enzyme-I inhibitors by 2D-QSAR and constraint-based molecular simulations

Cardiovascular diseases (CVD) such as heart failure, stroke, and hypertension affect 64.3 million people worldwide and are responsible for 30% of all deaths. Primary inhibition of the angiotensin-converting enzyme (ACE) is significant in the management of CVD. In the present study, the genetic algorithm-multiple linear regressions (GA-MLR) method is used to generate highly predictive and statistically significant (R2 = 0.70-0.75, Q2LOO=0.67-0.73, Q2LMO=0.66-0.72, CCCex=0.70-0.78) quantitative structure-activity relationships (QSAR) models conferring to OECD requirements using a dataset of 255 structurally diverse and experimentally validated ACE inhibitors. The models contain simply illustratable Padel, Estate, and PyDescriptors that correlate structural scaffold requisite for ACE inhibition. Also, constraint-based molecular docking reveals an interaction profile between ligands and enzymes which is then correlated with the essential structural features associated with the QSAR models. The QSAR-based virtual screening was utilized to find novel lead molecules from a designed database of 102 thiadiazole derivatives. The Applicability domain (AD), Molecular Docking, Molecular dynamics, and ADMET analysis suggest two compound D24 and D40 are inflexibly linked to the protein binding site and follows drug-likeness properties.Communicated by Ramaswamy H. Sarma.

In silico approach for the development of novel antiviral compounds based on SARS-COV-2 protease inhibition

The COVID-19 pandemic emerged in 2019, bringing with it the need for greater stores of effective antiviral drugs. This paper deals with the conformation-independent, QSAR model, developed by employing the Monte Carlo optimization method, as well as molecular graphs and the SMILES notation-based descriptors for the purpose of modeling the SARS-CoV-3CLpro enzyme inhibition. The main purpose was developing a reproducible model involving easy interpretation, utilized for a quick prediction of the inhibitory activity of SAR-CoV-3CLpro. The following statistical parameters were present in the best-developed QSAR model: (training set) R 2 = 0.9314, Q 2 = 0.9271; (test set) R 2 = 0.9243, Q 2 = 0.8986. Molecular fragments, defined as SMILES notation descriptors, that have a positive and negative impact on 3CLpro inhibition were identified on the basis of the results obtained for structural indicators, and were applied to the computer-aided design of five new compounds with (4-methoxyphenyl)[2-(methylsulfanyl)-6,7-dihydro-1H-[1,4]dioxino[2,3-f]benzimidazol-1-yl]methanone as a template molecule. Molecular docking studies were used to examine the potential inhibition effect of designed molecules on SARS-CoV-3CLpro enzyme inhibition and obtained results have high correlation with the QSAR modeling results. In addition, the interactions between the designed molecules and amino acids from the 3CLpro active site were determined, and the energies they yield were calculated.

Supplementary Information

The online version contains supplementary material available at 10.1007/s11696-022-02170-8.

Considerations for Docking of Selective Angiotensin-Converting Enzyme Inhibitors

The angiotensin-converting enzyme (ACE) is a two-domain dipeptidylcarboxypeptidase, which has a direct involvement in the control of blood pressure by performing the hydrolysis of angiotensin I to produce angiotensin II. At the same time, ACE hydrolyzes other substrates such as the vasodilator peptide bradykinin and the anti-inflammatory peptide N-acetyl-SDKP. In this sense, ACE inhibitors are bioactive substances with potential use as medicinal products for treatment or prevention of hypertension, heart failures, myocardial infarction, and other important diseases. This review examined the most recent literature reporting ACE inhibitors with the help of molecular modeling. The examples exposed here demonstrate that molecular modeling methods, including docking, molecular dynamics (MD) simulations, quantitative structure-activity relationship (QSAR), etc, are essential for a complete structural picture of the mode of action of ACE inhibitors, where molecular docking has a key role. Examples show that too many works identified ACE inhibitory activities of natural peptides and peptides obtained from hydrolysates. In addition, other works report non-peptide compounds extracted from natural sources and synthetic compounds. In all these cases, molecular docking was used to provide explanation of the chemical interactions between inhibitors and the ACE binding sites. For docking applications, most of the examples exposed here do not consider that: (i) ACE has two domains (nACE and cACE) with available X-ray structures, which are relevant for the design of selective inhibitors, and (ii) nACE and cACE binding sites have large dimensions, which leads to non-reliable solutions during docking calculations. In support of the solution of these problems, the structural information found in Protein Data Bank (PDB) was used to perform an interaction fingerprints (IFPs) analysis applied on both nACE and cACE domains. This analysis provides plots that identify the chemical interactions between ligands and both ACE binding sites, which can be used to guide docking experiments in the search of selective natural components or novel drugs. In addition, the use of hydrogen bond constraints in the S₂ and S₂′ subsites of nACE and cACE are suggested to guarantee that docking solutions are reliable.

Advances in Structural Biology of ACE and Development of Domain Selective ACE-inhibitors

BACKGROUND

The Angiotensin-I converting enzyme (ACE) is one of the most important components of the renin-angiotensin-aldosterone system controlling blood pressure and renal functions. Inhibitors of ACE are first line therapeutics used in the treatment of hypertension and related cardiovascular diseases. Somatic ACE consists of two homologous catalytic domains, the C- and N-domains. Recent findings have shown that although both domains are highly homologous in structure, they may have different physiological functions. The C-domain is primarily involved in the control of blood pressure, in contrast to the N-domain that is engaged in the regulation of hematopoietic stem cell proliferation. The currently available ACE inhibitors have some adverse effects that can be attributed to the non-selective inhibition of both domains. In addition, specific Ndomain inhibitors have emerged as potential antifibrotic drugs. Therefore, ACE is still an important drug target for the development of novel domain-selective drugs not only for the cardiovascular system but also for other systems.

OBJECTIVE

Detailed structural information about interactions in the protein-ligand complex is crucial for rational drug design. This review highlights the structural information available from crystallographic data which is essential for the development of domain selective inhibitors of ACE.

METHODS

Over eighty crystal complexes of ACE are placed into the Protein Database. An overview of X-ray ACE complexes with various inhibitors in C- and N-domains and an analysis of their binding mode have given mechanistic explanation of the structural determinants of selective ligand binding. In addition, ACE domain selective inhibitors with dual modes of action in complexes with ACE are also discussed.

CONCLUSION

Selectivity of ACE inhibitors for the N- and C-domain is controlled by subtle differences in the amino-acids forming the active site. Reported studies of crystal complexes of inhibitors in the C- and N-domains revealed that most selective inhibitors interact with non-conserved amino-acids between domains and have distinct interactions with the residues in the S2 and S2' subsites of the ACE catalytic site. Moreover, unusual binding of the second molecule of inhibitors in the binding cavity opens new possibilities of exploiting more distant regions of the catalytic center in structure-based design of novel drugs.