Target-based drug discovery, ADMET profiling and bioactivity studies of antibiotics as potential inhibitors of SARS-CoV-2 main protease (Mpro)

A recent outbreak of a new strain of Coronavirus (SARS-CoV-2) has become a global health burden, which has resulted in deaths. No proven drug has been found to effectively cure this fast-spreading infection, hence the need to explore old drugs with the known profile in tackling this pandemic. A computer-aided drug design approach involving virtual screening was used to obtain the binding scores and inhibiting efficiencies of previously known antibiotics against SARS-CoV-2 main protease (Mpro). The drug-likeness analysis of the repurposed drugs were done using the Molinspiration chemoinformatics tool, while the Absorption, Distribution, Metabolism, Excretion, and Toxicity (ADMET) analysis was carried out using ADMET SAR-2 webserver. Other analyses performed include bioactivities of the repurposed drug as a probable anti-SARS-CoV-2 agent and oral bioavailability analyses among others. The results were compared with those of drugs currently involved in clinical trials in the ongoing pandemic. Although antibiotics have been speculated to be of no use in the treatment of viral infections, literature has emerged lately to reveal the antiviral potential and immune-boosting ability of antibiotics. This study identified Tarivid and Ciprofloxacin with binding affinities of - 8.3 kcal/mol and - 8.1 kcal/mol, respectively as significant inhibitors of SARS-CoV-2 (Mpro) with better pharmacokinetics, drug-likeness and oral bioavailability, bioactivity properties, ADMET properties and inhibitory strength compared to Remdesivir (- 7.6 kcal/mol) and Azithromycin (- 6.3 kcal/mol). These observations will provide insight for further research (clinical trial) in the cure and management of COVID-19.

Unveiling novel inhibitors of dopamine transporter via in silico drug design, molecular docking, and bioavailability predictions as potential antischizophrenic agents

Background

The inhibition of dopamine transporter is known to play a significant role in the treatment of schizophrenia-related and other mental disorders. In a continuing from our previous study, computational drug design approach, molecular docking simulation, and pharmacokinetics study were explored for the identification of novel inhibitors dopamine transporter as potential Antischizophrenic agents. Consequently, thirteen (13) new inhibitors of dopamine transporter were designed by selecting the molecule with serial number 39 from our previous study as the template molecule because  it exhibits good pharmacological attributes.

Results

Molecular docking simulation results revealed excellent molecular interactions between the protein target (PDB: 4m48) and the ligands (designed inhibitors) with major interactions that involved hydrogen bonding and hydrophobic interactions. Also, some of the designed inhibitors displayed a superior binding affinity range from − 10.0 to − 10.7 kcal/mol compared to the referenced drug (Lumateperone) with a binding affinity of − 9.7 kcal/mol. Computed physicochemical parameters showed that none of the designed inhibitors including the referenced drug violate Lipinski’s rule of five indicating that all the designed inhibitors would be orally bioavailable as potential drug candidates. Similarly, the ADMET/pharmacokinetics evaluations of some designed inhibitors revealed that they possessed good absorption, distribution, metabolism and excretion properties and none of the inhibitors is neither carcinogens nor toxic toward human ether-a-go-go related gene (hERG I) inhibitor or skin sensitization. Likewise, the BOILED-Egg graphics unveils that all the designed inhibitors demonstrate a high probability to be absorbed by the human gastrointestinal tract and could permeate into the brain. Besides, the predicted bioactive parameters suggested that all the selected inhibitors would be active as drug candidates. Furthermore, the synthetic accessibility scores for all the selected inhibitors and referenced drug lied within the easy zone (i.e., between 1–4) with their computed values range from 2.55 to 3.92, this implies that all the selected inhibitors would be very easy to synthesize in the laboratory.

Conclusions

Hence, all the designed inhibitors having shown excellent pharmacokinetics properties and good bioavailabilities attributes with remarkable biochemical interactions could be developed and optimized as novel Antischizophrenic agents after the conclusion of other experimental investigations.

Chemoinformatic studies on some inhibitors of dopamine transporter and the receptor targeting schizophrenia for developing novel antipsychotic agents

Chemoinformatic studies were carried on some inhibitors of dopamine transporter to develop a predictive and robust QSAR model and also to elucidate binding mode and molecular interactions between the ligands (inhibitors) and the receptor targeting schizophrenia as novel Antipsychotic agents. Density Functional Theory (DFT) approach was utilized to optimize the ligands at B3LYP/6-31G∗ at the ground state and Multi-linear regression of the genetic function approximation (MLR-GFA) method was employed in building Penta-parametric linear equation models. The best model with statistically significant parameters has squared correlation coefficient R²= 0.802, adjusted squared correlation coefficient R²_adj = 0.767, Leave one out (LOO) cross-validation coefficient (Q²) = 0.693, lack of fit score (LOF) = 0.406, R²_Test = 0.77, Y-randomization test (cR²p) = 0.714, Chi-squared (χ²) =0.026, bootstrapping (Systematic errors = 0.272) and Variance Inflation Factor (VIF) <2 . The obtained results were compared with standard validation parameters to ascertain the predictivity, reliability, and robustness of the model. Also, the mechanistic interpretation of the descriptors found in the model revealed that two out of five descriptors; MATS7s (32.3%) and RDF95m (30.4%) having pronounced influence on the observed antipsychotic property of the compounds evidenced by their highest percentage contributions. More so, the molecular docking investigation showed that the binding affinity of the selected ligands ranges from -10.05 to -9.0 kcal/mol and with ligand 21 possessed the highest binding affinity (-10.05 kcal/mol). Furthermore, all the selected ligands displayed hydrogen bonds and hydrophobic interactions with the amino acid residues of the target (4M48) which could account for their higher binding energy. Our findings revealed that the developed model passed the general requirements for an acceptable QSAR model and also satisfied the OECD principles for model development. Hence, the developed model would be practically useful as a blueprint in developing novel antipsychotic agents with improved activity for the treatment of schizophrenia mental disorder.

QSAR modeling, molecular docking and ADMET/pharmacokinetic studies: a chemometrics approach to search for novel inhibitors of norepinephrine transporter as potent antipsychotic drugs

Chemometrics study that relates biological activity to physicochemical descriptors of a molecule and the prediction of absorption, distribution, metabolism, excretion and toxicity (ADMET) properties in advance are important steps in drugs discovery. In this study, a chemometrics approach was employed on some molecules (inhibitors) of norepinephrine transporter to assess their inhibitory potencies, interactions with the receptor and predict their ADMET/pharmacokinetic properties for identification of novel antipsychotic drugs. The molecules were optimized by using density functional theory at the basis set of B3LYP/6-31G*. The genetic function algorithm technique was used to generate a statistically significant model with a good correlation coefficient R2Train = 0.952 Cross-validated coefficient Q2cv = 0.870, and adjusted squared correlation coefficient R2adj = 0.898. The molecular docking simulation using a neurotransmitter transporter receptor (PDB Code 2A65) revealed that three inhibitors (molecule No 38, 44 and 12) exhibited the highest binding affinity of − 10.3, − 9.9 and − 9.3 kcal/mol, respectively, were observed to inhibit the target by forming strong hydrogen bonds with hydrophobic interactions. The physicochemical and ADMET/pharmacokinetic properties result showed that these three molecules are orally bioavailable, high gastrointestinal absorption, good permeability and non-inhibitors of CYP3A4 and CYP2D6 except for molecule No 38. Also, Molecules No 38 and 44 proved to be non-substrate of P-glycoprotein and nontoxicity to a human ether-a-go-go-related gene with predicted hERG toxicity endpoints (pIC50 < 6) and low ADMET_Risk (< 7.0). The results of this study would provide physicochemical and pharmacokinetics properties needed to identify potent antipsychotic drugs and other relevant information in drug discovery.

QSAR analysis and molecular docking simulation of norepinephrine transporter (NET) inhibitors as anti-psychotic therapeutic agents

The norepinephrine transporter (NET) is a Na+/Cl- coupled neurotransmitter transporter responsible for reuptake of released norepinephrine (NE) into nerve terminals in the brain, a key therapeutic used in the treatment of psychiatric disorders. A quantitative structural activity relationship (QSAR) study was performed on 50 compounds of NET inhibitors to investigate their inhibitory potencies against norepinephrine transporter as novel drugs for anti-psychotic disorders. The compounds were optimized by employing Density functional theory (DFT) with basis set of B3LYP/6-31G*. The genetic function Algorithm (GFA) approach was used to generate a highly predictive and statistically significant model with good correlation coefficient R2 Train = 0.952 Cross validated coefficient Q2 cv = 0.870 and adjusted squared correlation coefficient R2 adj = 0.898. The predictability and accuracy of the developed model was evaluated through external validation using test set compound, Y-randomization and applicability domain techniques. The results of Molecular docking analysis by using two neurotransmitter transporters PDB ID 2A65 (resolution = 1.65 Å) and PDB ID 4M48 (resolution = 2.955 Å) showed that two of the ligands (compound 12 and 44) having higher binding affinity were observed to inhibit the targets by forming hydrogen bonds and hydrophobic interactions with amino acids of the two receptors respectively. The results of these studies would provide important new insight into the molecular basis and structural requirements to design more potent and more specific therapeutic anti-psychotic drugs/agents.