Application of 3D QSAR CoMFA/CoMSIA and in silico docking studies on novel renin inhibitors against cardiovascular diseases

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.

Insights into the structural requirements of triazole derivatives as promising DPP IV inhibitors: computational investigations

Diabetes is one of the leading causes of death globally as per World Health Organization 2019. To cope up with side effects of current diabetes therapy, researchers have found several novel targets for the treatment of diabetes. Currently, dipeptidyl peptidase IV (DPP IV) has emerged as a target in modulating the diabetes physiology. In the present work, various 3D-Quantitative structure activity relationship (QSAR) techniques namely comparative molecular field analysis (CoMFA), comparative molecular similarity indices analysis, topomer CoMFA and molecular hologram QSAR are used to explore the structural requirements of triazole derivatives as DPP IV inhibitors. Different models generated by 3D QSAR studies had acceptable statistical values for further prediction of molecules. From the contour maps of QSAR results, important structural features are deduced. Substitutions on N₁ and N₂ of triazole ring with H-bond donor group enhances the biological activity. Aliphatic side chain, less bulky group, H-bond donor group and -COOH group on N₃ of triazole ring are vital for the DPP IV inhibition. Moreover, electron withdrawing side chain on the triazole ring improves the biological activity. Further, novel triazole derivatives were designed and docking results of these compounds proved the efficiency of the developed 3D QSAR model. In future, results of this study may provide promising DPP IV inhibitors for the treatment of diabetes. Communicated by Ramaswamy H. Sarma.

Anticholinesterase Inhibition, Drug-Likeness Assessment, and Molecular Docking Evaluation of Milk Protein-Derived Opioid Peptides for the Control of Alzheimer’s Disease

The drug-likeness and pharmacokinetic properties of 23 dairy-protein-derived opioid peptides were studied using SwissADME and ADMETlab in silico tools. All the opioid peptides had poor drug-like properties based on violations of Lipinski’s rule-of-five. Moreover, prediction of their pharmacokinetic properties showed that the peptides had poor intestinal absorption and bioavailability. Following this, two well-known opioid peptides (βb-casomorphin-5, βb-casomorphin-7) from A1 bovine milk and caffeine (positive control) were selected for in silico molecular docking and in vitro inhibition study with two cholinesterase enzyme receptors important for the pathogenesis of Alzheimer’s disease. Both peptides showed higher binding free energies and inhibitory activities to butyrylcholinesterase (BChE) than caffeine, but in vitro binding energy values were lower than those from the docking model. Moreover, the two casomorphins had lower inhibitory properties against acetylcholinesterase (AChE) than caffeine, although the docking model predicted the opposite. At 1 mg/mL concentrations, βb-casomorphin-5 and βb-casomorphin-7 showed promising results in inhibiting both cholinesterases (i.e., respectively 34% and 43% inhibition of AChE, and 67% and 81% inhibition of BChE). These dairy-derived opioid peptides have the potential to treat Alzheimer’s disease via cholinesterase inhibition. However, appropriate derivatization may be required to improve their poor predicted intestinal absorption and bioavailability.

Is conformation relevant for QSAR purposes? 2D Chemical representation in a 3D-QSAR perspective

Conformation has a key role in the mechanism of interaction between small molecules and biological receptors. However, encoding this type of information in molecular descriptors for the construction of robust quantitative structure-activity relationships (QSAR) models is not an easy task and, so far, the dependence of these models on such feature has not been thoroughly investigated. In the present study, the authors explore the effects of conformational information on a 3D-QSAR technique by comparing models built with descriptors that encode fully described tridimensional aspects (structures docked inside a biological target), with descriptors in which this information is suppressed (flat structures) or not fully described (structures with quantum-chemically optimized geometries). As a result, the validation parameters indicate that the robustness of the models seems to be more related to the alignment aspect of the structures than to how well their tridimensional features are described.

Part-II- in silico drug design: application and success

In silico tools have indeed reframed the steps involved in traditional drug discovery and development process and the term in silico has become a familiar term in pharmaceutical sector like the terms in vitro and in vivo. The successful design of HIV protease inhibitors, Saquinavir, Indinavir and other important medicinal agents, initiated interest of researchers in structure based drug design approaches (SBDD). The interactions between biomolecules and a ligand, binding energy, free energy and stability of biomolecule-ligand complex can be envisioned and predicted by applying molecular docking studies. Protein-ligand, protein-protein, DNA-ligand interactions etc. aid in elucidating molecular level mechanisms of drug molecules. In the Ligand based drug design (LBDD) approaches, QSAR studies have tremendously contributed to the development of antimicrobial, anticancer, antimalarial agents. In the recent years, multiQSAR (mt-QSAR) approaches have been successfully employed for designing drugs against multifactorial diseases. Output of a research in several instances is rewarding when both SBDD and LBDD approaches are combined. Application of in silico studies for prediction of pharmacokinetics was once a real challenge but one can see unlimited number publications comprising tools, data bases which can accurately predict almost all the pharmacokinetic parameters. Absorption, distribution, metabolism, transporters, blood brain barrier permeability, hERG toxicity, P-gp affinity and several toxicological end points can be accurately predicted for a candidate molecule before its synthesis. In silico approaches are greatly encouraged a result of growing limitations and new legislations related to the animal use for research. The combined use of in vitro data and in silico tools will definitely decrease the use of animal testing in the future.In this chapter, in silico approaches and their applications are reviewed and discussed giving suitable examples.

Physicochemical characterisation, molecular docking, and drug-likeness evaluation of hypotensive peptides encrypted in flaxseed proteome

In this study, hypotensive peptides derived from mature flaxseed protein sequences were predicted in silico using BIOPEP-UWM with nine proteases, three each from digestive, plant and microbial sources. The physicochemical properties of 2256 ACE-inhibitory peptides and 267 renin-inhibitory peptides (including seven (7) peptides with dual inhibitory activities against both ACE and renin enzymes) were assessed in silico using the ‘Peptides’ package of R. The hypotensive peptides showed relatively low molecular weight (mol. wt.) range (132 = mol. wt. ≤ 442 Da); broad range of isoelectric point (3.61 = pI ≤ 12.50); both high (>2) and low (≤2) Boman indices, and a variety of hydrophobicity indices (hydrophilic, hydrophobic and amphipathic properties). Following this, the seven peptides with dual ACE and renin inhibitory activities were selected for molecular docking with the respective enzyme receptors. The binding energies of the seven hypotensive peptides with ACE and renin respectively ranged from −36.82 to −25.94 kJ/mol, and −33.05 to −27.61 kJ/mol; and compared well with values recorded for inhibitor drugs, captopril (−26.78 kJ/mol) and aliskiren (−34.73 kJ/mol). The seven peptides inhibited ACE through hydrogen bonds, electrostatic and hydrophobic interactions; and renin, mainly through hydrogen bonds and hydrophobic interactions. In silico prediction of adsorption, digestion, metabolism, excretion and toxicity (ADME/Tox) profile based on physicochemical properties and Lipinski's rule-of-five showed that the peptides were non-toxic and had desirable drug-like properties (flexibility, lipophilicity, molecular weight, gastrointestinal absorption, and bioavailability). This study provides insight into the molecular interactions of hypotensive peptides with their physiological targets, and the potential to develop the bioactive peptides from flaxseed proteins.

•

Flaxseed proteins were assessed in silico as source of hypotensive peptides.

•

Plant proteases were most suitable to release hypotensive peptides in silico.

•

Hypotensive peptides had molecular docking features similar to captopril and aliskiren.

•

In silico-derived hypotensive

peptides were non-toxic, and had drug-like properties.

Exploring the structural determinants of novel xanthine derivatives as A2B adenosine receptor antagonists: a computational study

Adenosine is a ubiquitous endogenous nucleoside that controls numerous physiological functions via interacting with its specific G-coupled receptors. Activation of adenosine receptors (AdoRs), particularly A_2B AdoRs promotes the release of inflammatory cytokines; reduces vascular permeabilization and induces angiogenesis, thereby making A_2B AdoR becomes a potentially pharmacological target for drug development. Presently, for investigating the structural determinants of 164 xanthine derivatives as A_2B AdoR antagonists, we performed an in silico study integrating with 3D-QSAR, docking and molecular dynamics (MD) simulation. The obtained optimal model shows strong predictability (Q² = 0.647, R²_ncv = 0.955, and R²_pred = 0.848). Additionally, to explore the binding mode of the ligand with A_2B AdoR and to understand their binding mechanism, docking analysis, MD simulations (20 ns), and the calculation of binding free energy were also carried out. Finally, the structural determinants of these xanthine derivatives were identified and a total of 20 novel A_2B AdoR antagonists with improved potency were computationally designed, and their synthetic feasibility and selectivity were also evaluated. The information derived from the present study offers a better appreciation for exploring the interaction mechanism of the ligand with A_2B AdoR, which could be helpful for designing novel potent A_2B AdoR antagonists. Communicated by Ramaswamy H. Sarma.

New molecular insights into the tyrosyl-tRNA synthase inhibitors: CoMFA, CoMSIA analyses and molecular docking studies

Drug resistance caused by excessive and indiscriminate antibiotic usage has become a serious public health problem. The need of finding new antibacterial drugs is more urgent than ever before. Tyrosyl-tRNA synthase was proved to be a potent target in combating drug-resistant bacteria. In silico methodologies including molecular docking and 3D-QSAR were employed to investigate a series of newly reported tyrosyl-tRNA synthase inhibitors of furanone derivatives. Both internal and external cross-validation were conducted to obtain high predictive and satisfactory CoMFA model (q 2 = 0.611, r 2pred  = 0.933, r 2m  = 0.954) and CoMSIA model (q 2 = 0.546, r 2pred  = 0.959, r 2m  = 0.923). Docking results, which correspond with CoMFA/CoMSIA contour maps, gave the information for interactive mode exploration. Ten new molecules designed on the basis of QSAR and docking models have been predicted more potent than the most active compound 3-(4-hydroxyphenyl)-4-(2-morpholinoethoxy)furan-2(5H)-one (15) in the literatures. The results expand our understanding of furanones as inhibitors of tyrosyl-tRNA synthase and could be helpful in rationally designing of new analogs with more potent inhibitory activities.

The signaling pathway of dopamine D2 receptor (D2R) activation using normal mode analysis (NMA) and the construction of pharmacophore models for D2R ligands

G-protein-coupled receptors (GPCRs) are targets of more than 30% of marketed drugs. Investigation on the GPCRs may shed light on upcoming drug design studies. In the present study, we performed a combination of receptor- and ligand-based analysis targeting the dopamine D2 receptor (D2R). The signaling pathway of D2R activation and the construction of universal pharmacophore models for D2R ligands were also studied. The key amino acids, which contributed to the regular activation of the D2R, were in detail investigated by means of normal mode analysis (NMA). A derived cross-correlation matrix provided us an understanding of the degree of pair residue correlations. Although negative correlations were not observed in the case of the inactive D2R state, a high degree of correlation appeared between the residues in the active state. NMA results showed that the cytoplasmic side of the TM5 plays a significant role in promoting of residue-residue correlations in the active state of D2R. Tracing motions of the amino acids Arg219, Arg220, Val223, Asn224, Lys226, and Ser228 in the position of the TM5 are found to be critical in signal transduction. Complementing the receptor-based modeling, ligand-based modeling was also performed using known D2R ligands. The top-scored pharmacophore models were found as 5-sited (AADPR.671, AADRR.1398, AAPRR.3900, and ADHRR.2864) hypotheses from PHASE modeling from a pool consisting of more than 100 initial candidates. The constructed models using 38 D2R ligands (in the training set) were validated with 15 additional test set compounds. The resulting model correctly predicted the pIC₅₀ values of an additional test set compounds as true unknowns.

Identification of potential quinoxalinone-based aldose reductase inhibitors by 3D-QSAR, molecular docking and molecular dynamics

The 3D-QSAR model of aldose reductase (ARIs) inhibitors is built to gain insights into the key structural factors affecting the inhibitory activity. Based on the model, six new potential ARIs were designed.

Pharmacodynamics and potential synergistic effects of Mai-Luo-Ning injection on cardiovascular protection, based on molecular docking

As a computer-assisted approach, molecular docking has been universally applied in drug research and development and plays an important role in the investigation and evaluation of herbal medicines. Herein, the method was used to estimate the pharmacodynamics of Mai-Luo-Ning injection, a traditional Chinese compound herbal prescription. Through investigating the interactions between several important proteins in cardiovascular system and characteristic components of the formula, its effect on cardiovascular protection was evaluated. Results showed the differences in the interactions between each component and the selected target proteins and revealed the possible mechanisms for synergistic effects of various characteristic components on cardiovascular protection. The study provided scientific evidence supporting the mechanistic study of the interactions among multi-components and targets, offering a general approach to investigating the pharmacodynamics of complicated materials in compound herbal prescriptions.

Binding mode prediction and identification of new lead compounds from natural products as renin and angiotensin converting enzyme inhibitors

In this study a novel renin and ACE inhibitor was developed from natural products using computational techniques. Molecular dynamic simulations showed that the new lead compound has significant binding to the targets.

2-(1-Amino-4-tert-butyl-cyclo-hex-yl)acetic acid (tBu-β(3,3)-Ac6c) hemihydrate

The title compound, C12H23NO2·0.5H2O, crystallized with two 2-(1-amino-4-tert-butylcyclohexyl)acetic acid mol-ecules, which are present as zwitterions, and one water mol-ecule in the asymmetric unit. The mol-ecular structure of each zwitterion is stabilized by an intra-molecular six-membered (C 6 ) N-H⋯O hydrogen bond. In the crystal, the two independent zwitterions are linked head-to-head by N-H⋯O hydrogen bonds. Further O-H⋯O and N-H⋯O hydrogen bonds link the zwitterions and the water molecules, forming sandwich-like layers, with a hydrophilic filling and a hydrophobic exterior, lying parallel to the ab plane.

Molecular dynamics studies on both bound and unbound renin protease

The aspartic protease renin (REN) catalyses the rate-limiting step in the Renin-Angiotensin-Aldosterone System (RAAS), which regulates cardiovascular and renal homoeostasis in living organisms. Renin blockage is therefore an attractive therapeutic strategy for the treatment of hypertension. Herein, computational approaches were used to provide a structural characterization of the binding site, flap opening and dynamic rearrangements of REN in the key conserved residues and water molecules, with the binding of a dodecapeptide substrate or different inhibitors. All these structural insights during catalysis may assist future studies in developing novel strategies for REN inactivation. Our molecular dynamics simulations of several unbound-REN and bound-REN systems indicate similar flexible-segments plasticity with larger fluctuations in those belonging to the C-domain (exposed to the solvent). These segments are thought to assist the flap opening and closure to allow the binding of the substrate and catalytic water molecules. The unbound-REN simulation suggests that the flap can acquire three different conformations: closed, semi-open and open. Our results indicate that the semi-open conformation is already sufficient and appropriate for the binding of the angiotensinogen (Ang) tail, thus contributing to the high specificity of REN, and that both semi-open and open flap conformations are present in free and complexed enzymes. We additionally observed that the Tyr75-Trp39 H-bond has an important role in assisting flap movement, and we highlight several conserved water molecules and amino acids that are essential for the proper catalytic activity of REN.

The catalytic mechanism of mouse renin studied with QM/MM calculations

Hypertension is a chronic condition that affects nearly 25% of adults worldwide. As the Renin-Angiotensin-Aldosterone System is implicated in the control of blood pressure and body fluid homeostasis, its combined blockage is an attractive therapeutic strategy currently in use for the treatment of several cardiovascular conditions. We have performed QM/MM calculations to study the mouse renin catalytic mechanism in atomistic detail, using the N-terminal His6-Asn14 segment of angiotensinogen as substrate. The enzymatic reaction (hydrolysis of the peptidic bond between residues in the 10th and 11th positions) occurs through a general acid/base mechanism and, surprisingly, it is characterized by three mechanistic steps: it begins with the creation of a first very stable tetrahedral gem-diol intermediate, followed by protonation of the peptidic bond nitrogen, giving rise to a second intermediate. In a final step the peptidic bond is completely cleaved and both gem-diol hydroxyl protons are transferred to the catalytic dyad (Asp32 and Asp215). The final reaction products are two separate peptides with carboxylic acid and amine extremities. The activation energy for the formation of the gem-diol intermediate was calculated as 23.68 kcal mol(-1), whereas for the other steps the values were 15.51 kcal mol(-1) and 14.40 kcal mol(-1), respectively. The rate limiting states were the reactants and the first transition state. The associated barrier (23.68 kcal mol(-1)) is close to the experimental values for the angiotensinogen substrate (19.6 kcal mol(-1)). We have also tested the influence of the density functional on the activation and reaction energies. All eight density functionals tested (B3LYP, B3LYP-D3, X3LYP, M06, B1B95, BMK, mPWB1K and B2PLYP) gave very similar results.

Development, evaluation and application of 3D QSAR Pharmacophore model in the discovery of potential human renin inhibitors

Background

Renin has become an attractive target in controlling hypertension because of the high specificity towards its only substrate, angiotensinogen. The conversion of angiotensinogen to angiotensin I is the first and rate-limiting step of renin-angiotensin system and thus designing inhibitors to block this step is focused in this study.

Methods

Ligand-based quantitative pharmacophore modeling methodology was used in identifying the important molecular chemical features present in the set of already known active compounds and the missing features from the set of inactive compounds. A training set containing 18 compounds including active and inactive compounds with a substantial degree of diversity was used in developing the pharmacophore models. A test set containing 93 compounds, Fischer randomization, and leave-one-out methods were used in the validation of the pharmacophore model. Database screening was performed using the best pharmacophore model as a 3D structural query. Molecular docking and density functional theory calculations were used to select the hit compounds with strong molecular interactions and favorable electronic features.

Results

The best quantitative pharmacophore model selected was made of one hydrophobic, one hydrogen bond donor, and two hydrogen bond acceptor features with high a correlation value of 0.944. Upon validation using an external test set of 93 compounds, Fischer randomization, and leave-one-out methods, this model was used in database screening to identify chemical compounds containing the identified pharmacophoric features. Molecular docking and density functional theory studies have confirmed that the identified hits possess the essential binding characteristics and electronic properties of potent inhibitors.

Conclusion

A quantitative pharmacophore model of predictive ability was developed with essential molecular features of a potent renin inhibitor. Using this pharmacophore model, two potential inhibitory leads were identified to be used in designing novel and future renin inhibitors as antihypertensive drugs.

Docking alignment-3D-QSAR of a new class of potent and non-chiral indole-3-carboxamide-based renin inhibitors

Using generated conformations from docking analysis by CDOCKER algorithm, some 3D-QSAR models; CoMFA region focusing (CoMFA-RF) and CoMSIA have been created on a series of a new class of potent and non-chiral renin inhibitors. The satisfactory predictions were obtained by CoMFA-RF and CoMSIA based on docking alignment in comparison to CoMFA. Robustness and predictability of the models were further verified by using the test set, cross validation (leave one out and leave ten out), bootstrapping, and progressive scrambling. All-orientation search (AOS) strategy was used to acquire the best orientation and minimize the effect of the initial orientation of aligned compounds. The results of 3D-QSAR models are in agreement with docking results. Moreover, the resulting 3D CoMFA-RF/ CoMSIA contour maps and corresponding models were applied to design new and more active inhibitors.

Molecular modeling studies on 11H-dibenz[b,e]azepine and dibenz[b,f][1,4]oxazepine derivatives as potent agonists of the human TRPA1 receptor

A computational strategy based on comparative molecular fields analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) was performed on a series of the 11H-dibenz[b,e]azepine and dibenz[b,f][1,4]oxazepine derivatives as potent agonists of the human TRPA1 receptor. The CoMFA and CoMSIA models resulting from a 21 molecule training set gave r²(cv) values of 0.631 and 0.542 and r² values of 0.986 and 0.981, respectively. The statistically significant models were validated by a test set of five compounds with predictive r²(pred). values of 0.967 and 0.981 for CoMFA and CoMSIA, respectively. A systemic external validation was also performed on the established models. The information obtained from 3D counter maps could facilitate the design of more potent human TRPA1 receptor agonists.

Molecular modeling studies of 4,5-dihydro-1H-pyrazolo[4,3-h] quinazoline derivatives as potent CDK2/Cyclin a inhibitors using 3D-QSAR and docking

CDK2/cyclin A has appeared as an attractive drug targets over the years with diverse therapeutic potentials. A computational strategy based on comparative molecular fields analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) followed by molecular docking studies were performed on a series of 4,5-dihydro-1H-pyrazolo[4,3-h]quinazoline derivatives as potent CDK2/cyclin A inhibitors. The CoMFA and CoMSIA models, using 38 molecules in the training set, gave r(2) (cv) values of 0.747 and 0.518 and r(2) values of 0.970 and 0.934, respectively. 3D contour maps generated by the CoMFA and CoMSIA models were used to identify the key structural requirements responsible for the biological activity. Molecular docking was applied to explore the binding mode between the ligands and the receptor. The information obtained from molecular modeling studies may be helpful to design novel inhibitors of CDK2/cyclin A with desired activity.