Drug-likeness Prediction Research Articles

Flavanones: A potential natural inhibitor of the ATP binding site of PknG of Mycobacterium tuberculosis

Over the years, Mycobacterium tuberculosis has been one of the major causes of death worldwide. As several clinical isolates of the bacteria have developed drug resistance against the target sites of the current therapeutic agents, the development of a novel drug is the pressing priority. According to recent studies on Mycobacterium tuberculosis, ATP binding sites of Mycobacterium tuberculosis serine/threonine protein kinases (MTPKs) have been identified as the new promising drug target. Among the several other protein kinases (PKs), Protein kinase G (PknG) was selected for the study because of its crucial role in modulating bacterium’s metabolism to survive in host macrophages. In this work, we have focused on the H37Rv strain of Mycobacterium tuberculosis. A list of 477 flavanones obtained from the PubChem database was docked one by one against the crystallized and refined structure of PknG by in-silico techniques. Initially, potential inhibitors were narrowed down by preliminary docking. Flavanones were then selected using binding energies ranging from −7.9 kcal.mol−1 to −10.8 kcal.mol−1. This was followed by drug-likeness prediction, redocking analysis, and molecular dynamics simulations. Here, we have used experimentally confirmed drug AX20017 as a reference to determine candidate compounds that can act as potential inhibitors for PknG. PubChem165506, PubChem242065, PubChem688859, PubChem101367767, PubChem3534982, and PubChem42607933 were identified as possible target site inhibitors for PknG with a desirable negative binding energy of −8.1, −8.3, −8.4, −8.8, −8.6 and −7.9 kcal.mol−1 respectively. Communicated by Ramaswamy H. Sarma

SARS-CoV-2 host cell entry: an in silico investigation of potential inhibitory roles of terpenoids

BackgroundTargeting viral cell entry proteins is an emerging therapeutic strategy for inhibiting the first stage of SARS-CoV-2 infection. In this study, 106 bioactive terpenoids from African medicinal plants were screened through molecular docking analysis against human angiotensin-converting enzyme 2 (hACE2), human transmembrane protease serine 2 (TMPRSS2), and the spike (S) proteins of SARS-CoV-2, SARS-CoV, and MERS-CoV. In silico absorption-distribution-metabolism-excretion-toxicity (ADMET) and drug-likeness prediction, molecular dynamics (MD) simulation, binding free energy calculations, and clustering analysis of MD simulation trajectories were performed on the top docked terpenoids to respective protein targets. ResultsThe results revealed eight terpenoids with high binding tendencies to the catalytic residues of different targets. Two pentacyclic terpenoids (24-methylene cycloartenol and isoiguesteri) interacted with the hACE2 binding hotspots for the SARS-CoV-2 spike protein, while the abietane diterpenes were found accommodated within the S1-specificity pocket, interacting strongly with the active site residues TMPRSS2. 3-benzoylhosloppone and cucurbitacin interacted with the RBD and S2 subunit of SARS-CoV-2 spike protein respectively. These interactions were preserved in a simulated dynamic environment, thereby, demonstrating high structural stability. The MM-GBSA binding free energy calculations corroborated the docking interactions. The top docked terpenoids showed favorable drug-likeness and ADMET properties over a wide range of molecular descriptors. ConclusionThe identified terpenoids from this study provides core structure that can be exploited for further lead optimization to design drugs against SARS-CoV-2 cell-mediated entry proteins. They are therefore recommended for further in vitro and in vivo studies towards developing entry inhibitors against the ongoing COVID-19 pandemic.

Design, Synthesis, Molecular Docking and In silico Analysis of Some Novel 2-Amino-1, 3, 4-Thiadiazole Derivatives as Potent DNA Gyrase B Inhibitors

Introduction: Thiadiazole derivatives have been reported as a potent antimicrobial agent and the discovery of drug molecules for antimicrobial-resistant strains of Escherichia coli is still a vital challenge in the modern world. Objective: The objective of the present study is to design, synthesize and perform molecular docking studies and in-silico analysis of some novel 2-amino-1, 3, 4-thiadiazole derivatives with the aim of developing potential DNA gyrase B inhibitors. Materials and Methods: The compound 5-substituted-1, 3,4-thiadiazol-2-amine derivatives [compound 1a-1c] ; 5,6-Diphenyl- 2-[5-(substituted)-1,3,4-thiadiazol-2-yl amino]-2H -1,2,4-triazine- 3-thione derivatives [compound 2a-2c]; and propyl 3,4,5-trihydroxy-2,6-bis [5-(substituted)- 1,3,4-thiadiazol-2-yl amino] benzoate derivatives [compound 3a -3c] were synthesised by temperature- controlled microwave-assisted method. The structures of the synthesized compounds were drawn in ChemSketch. Further, molecular docking and in-silico studies for the prediction of druglikeness, pharmacokinetic parameters and prediction of toxicity were carried out . The structures of the synthesized compounds were characterized by FT-IR, 1H NMR and mass spectral analysis. Results: The synthesized compounds had a better yield.The docking studies of the synthesized compounds had a better docking score with a good binding affinity towards the protein molecule. The synthesized compounds also comply with the in-silico prediction of drug-likeness, pharmacokinetic parameters and prediction of toxicity. Conclusion: The present study reveals that the 5-substituted-1, 3,4-thiadiazol-2-amine derivatives can serve as a better lead as potent DNA gyrase B inhibitor in further drug discovery.

Virtual Screening, Molecular Docking and In silico ADME-Tox Analysis for Identification of Potential Main Protease (Mpro) Enzyme Inhibitors

Objective: Recent pandemic caused by the SARS-CoV-2, first described in Wuhan city of China in December 2019, spread widely in almost all the countries of the world. Coronavirus (COVID-19) led to the unexpected death of many people and caused a severe economic loss in a number of countries. Virtual screening based on molecular docking, drug-likeness prediction, and in silico ADMET studies are some of the effective tools for the identification of small molecules as novel antiviral drugs to treat diseases. Methods: In the current study, virtual screening was performed through molecular docking for identifying potent inhibitors against Mpro enzyme from the ZINC library for the possible treatment of the COVID-19 pandemic. Interestingly, some compounds have been identified as possible anti-covid-19 agents for future research. A total of 350 compounds were screened based on their similarity score with reference compound X77 from ZINC data bank and were subjected to docking with crystal structure available of Mpro enzyme. These compounds were then filtered by their in silico ADME-Tox and drug-likeness prediction values. Result: Out of these 350 screened compounds, 10 compounds were selected based on their docking score and best-docked pose in comparison to the reference compound X77. In silico ADME-Tox and drug likeliness predictions of the top compounds were performed and showed excellent results. All the 10 screened compounds showed a significant binding pose with the target main protease (Mpro) enzyme and satisfactory pharmacokinetic and toxicological properties. Conclusion: Based on these results, it is suggested that the identified compounds may be considered for therapeutic development against the COVID-19 virus and can further be evaluated for in vitro activity, preclinical, clinical studies, and formulated in a suitable dosage form to maximize their bioavailability.

Targeting COVID-19 (SARS-CoV-2) main protease through active phytocompounds of ayurvedic medicinal plants - Emblica officinalis (Amla), Phyllanthus niruri Linn. (Bhumi Amla) and Tinospora cordifolia (Giloy) - A molecular docking and simulation study.

Coronavirus Disease-2019 (COVID-19), a viral disease caused by severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) was declared a global pandemic by WHO in 2020. In this scenario, SARS-CoV-2 main protease (COVID-19 Mpro), an enzyme mainly involved in viral replication and transcription is identified as a crucial target for drug discovery. Traditionally used medicinal plants contain a large amount of bioactives and pave a new path to develop drugs and medications for COVID-19. The present study was aimed to examine the potential of Emblica officinalis (amla), Phyllanthus niruri Linn. (bhumi amla) and Tinospora cordifolia (giloy) bioactive compounds to inhibit the enzymatic activity of COVID-19 Mpro. In total, 96 bioactive compounds were selected and docked with COVID-19 Mpro and further validated by molecular dynamics study. From the docking and molecular dynamics study, it was revealed that the bioactives namely amritoside, apigenin-6-C-glucosyl7-O-glucoside, pectolinarin and astragalin showed better binding affinities with COVID-19 Mpro. Drug-likeness, ADEMT and bioactivity score prediction of best drug candidates were evaluated by DruLiTo, pkCSM and Molinspiration servers, respectively. Overall, the in silico results confirmed that the validated bioactives could be exploited as promising COVID-19 Mpro inhibitors.

A Diarylpentanoid with Potential Activation of the p53 Pathway: Combination of in silico Screening Studies, Synthesis, and Biological Activity Evaluation.

In silico studies of a library of diarylpentanoids led us to the identification of potential new MDM2/X ligands. The diarylpentanoids with the best docking scores obeying the druglikeness and ADMET prediction properties were subsequently synthesized and evaluated for their antiproliferative activity on colon cancer HCT116 and fibroblasts HFF-1 cells. The effect on p53-MDM2/X interactions was evaluated through yeast-based assays for compounds showing potent antiproliferative activity in HCT116 cells and low toxicity in normal cells, resulting in the identification of a potential dual inhibitor. Moreover, its antiproliferative effect was significantly reduced in the absence of p53 and in MDA-MB-231 cells expressing a mutant p53 form. The antiproliferative effect of this compound was associated with induction of cell cycle arrest, apoptosis, PARP cleavage and increased p53 and its transcriptional targets, p21 and PUMA, in HCT116 cells. Docking poses and residues involved in the inhibition of p53-MDM2/X interactions were predicted by docking studies.

Benzylidene-6-hydroxy-3,4-dihydronaphthalenone chalconoids as potent tyrosinase inhibitors.

Background and purpose:Tyrosinase enzyme has a key role in melanin biosynthesis by converting tyrosine into dopaquinone. It also participates in the enzymatic browning of vegetables by polyphenol oxidation. Therefore, tyrosinase inhibitors are useful in the fields of medicine, cosmetics, and agriculture. Many tyrosinase inhibitors having drawbacks have been reported to date; so, finding new inhibitors is a great need.Experimental approach:A variety of 6-hydroxy-3,4-dihydronaphthalenone chalcone-like analogs (C1-C10) have been synthesized by aldol condensation of 6-hydroxy tetralone and differently substituted benzaldehydes. The compounds were evaluated for their inhibitory effect on mushroom tyrosinase by a spectrophotometric method. Moreover, the inhibition manner of the most active compound was determined by Lineweaver-Burk plots. Docking study was done using AutoDock 4.2. The drug-likeness scores and ADME features of the active derivatives were also predicted.Results/Findings:Most of the compounds showed remarkable inhibitory activity against the tyrosinase enzyme. 6-Hydroxy-2-(3,4,5-trimethoxybenzylidene)-3,4-dihydronaphthalen-1(2H)-one (C2) was the most potent derivative amongst the series with an IC50 value of 8.8 μM which was slightly more favorable to that of the reference kojic acid (IC50 = 9.7 μM). Inhibitory kinetic studies revealed that C2 behaves as a competitive inhibitor. According to the docking results, compound C2 formed the most stable enzyme-inhibitor complex, mainly via establishing interactions with the two copper ions in the active site. In silico drug-likeness and pharmacokinetics predictions for the proposed tyrosinase inhibitors revealed that most of the compounds including C2 have proper drug-likeness scores and pharmacokinetic properties.Conclusion and implications:Therefore, C2 could be suggested as a promising tyrosinase inhibitor that might be a good lead compound in medicine, cosmetics, and the food industry, and further drug development of this compound might be of great interest.

In Silico Approach Towards the Prediction of Drug-Likeness; Synthesis and In Vitro Evaluation of Biphenyl Derivatives

In Silico Approach Towards the Prediction of Drug-Likeness; Synthesis and In Vitro Evaluation of Biphenyl Derivatives

A merged molecular representation learning for molecular properties prediction with a web-based service

Deep learning has brought a dramatic development in molecular property prediction that is crucial in the field of drug discovery using various representations such as fingerprints, SMILES, and graphs. In particular, SMILES is used in various deep learning models via character-based approaches. However, SMILES has a limitation in that it is hard to reflect chemical properties. In this paper, we propose a new self-supervised method to learn SMILES and chemical contexts of molecules simultaneously in pre-training the Transformer. The key of our model is learning structures with adjacency matrix embedding and learning logics that can infer descriptors via Quantitative Estimation of Drug-likeness prediction in pre-training. As a result, our method improves the generalization of the data and achieves the best average performance by benchmarking downstream tasks. Moreover, we develop a web-based fine-tuning service to utilize our model on various tasks.

Rational design of flavonoid based potential inhibitors targeting SARS-CoV 3CL protease for the treatment of COVID-19

The current outbreak of Coronavirus Disease 2019 (COVID-19) pandemic has reported thousands of deaths worldwide due to the rapid transmission rate and the lack of antiviral drugs and vaccinations. There is an urgent need to develop potential antiviral drug candidates for the prevention of COVID-19 infection. In the present study, a series of potential inhibitors targeting SARS-CoV 3CL protease were rationally designed by incorporating gamma lactam ring, and various fluoro substituted heterocyclic ring systems to the flavonoid scaffold. The prediction of drug-likeness, oral bioavailability, toxicity, synthetic accessibility, and ADMET properties was made by computational means. Quercetin was used as standard. The binding affinity of the ligands towards the 3CL protease target was examined using docking simulations. The designed ligands possess favourable pharmacokinetic and pharmacodynamic properties. Ligand L4, L8, and L14 appeared to be the lead compounds in the series and can be considered for further in-vivo and in-vitro validation.

<i>In Silico</i> Functional and Structural Insight of Prenylated Pyrazolocurcumin Derivative Associated with the PGE<sub>2</sub> Inhibition through mPGES-1 Blocking

The search of novel mPGES-1 lead inhibitors has recently become subject of interest to medicinal chemists due to the safety in comparison to existing NSAIDs such as coxibs drugs. The recent published work revealed that prenylated pyrazolocurcumin derivative as mPGES-1 has been sucessfully designed and synthesized through computational guided 3D-QSAR approach. To improve our understanding, the present paper aimed to develop in silico functional and structural insight of the compound including pharmacophore mapping, molecular electrostatic potential (MEP) simulation using Density Functional Theory (DFT) and druglikeness prediction associated with PGE2 suppression through mPGES-1 blocking. The data collected from computational modelling studies provide important insight on the molecular conformation and further shed light towards structural modification of the future novel mPGES-1 inhibitors.

Quinazolinone-dihydropyrano[3,2-b]pyran hybrids as new α-glucosidase inhibitors: Design, synthesis, enzymatic inhibition, docking study and prediction of pharmacokinetic

A series of new quinazolinone-dihydropyrano[3,2-b]pyran derivatives 10A-L were synthesized by simple chemical reactions and were investigated for inhibitory activities against α-glucosidase and α-amylase. New synthesized compounds showed high α-glucosidase inhibition effects in comparison to the standard drug acarbose and were inactive against α-amylase. Among them, the most potent compound was compound 10L (IC50 value = 40.1 ± 0.6 µM) with inhibitory activity around 18.75-fold more than acarboase (IC50 value = 750.0 ± 12.5 µM). This compound was a competitive inhibitor into α-glucosidase. Our obtained experimental results were confirmed by docking studies. Furthermore, the cytotoxicity of the most potent compounds 10L, 10G, and 10N against normal fibroblast cells and in silico druglikeness, ADME, and toxicity prediction of these compounds were also evaluated.

Screening of JAK-STAT modulators from the antiviral plants of Indian traditional system of medicine with the potential to inhibit 2019 novel coronavirus using network pharmacology.

The majority of the bioactives under investigation were predicted to target TNF receptor-associated factor 5 in the Janus kinase/signal transducers and activators of the transcription pathway. Similarly, druglikeness prediction identified vitexilactone to possess the highest druglikeness score, i.e., 0.88. Furthermore, proteins targeted in the Janus kinase/signal transducers and activators of transcription pathway were also predicted to regulate multiple pathways, i.e., ErbB, AGE-RAGE, NF-kappa B, Measles, insulin, mTOR, chemokine, Ras, and pathways associated with infectious and non-infectious pathogenesis, where the immune system is compromised. Similarly, the docking study identified sesaminol 2-O-β-D-gentiobioside to possess the highest binding affinity with 3CLpro, PLpro, and spike proteins. Furthermore, phylogeny comparison identified the common protein domains with other stains of microbes like murine hepatitis virus strain A59, avian infectious bronchitis virus, and porcine epidemic diarrhea virus CV777.

Promising phytochemicals of traditional Indian herbal steam inhalation therapy to combat COVID-19 – An in silico study

BackgroundCOVID-19, the presently prevailing global public health emergency has culminated in international instability in economy. This unprecedented pandemic outbreak pressingly necessitated the trans-disciplinary approach in developing novel/new anti-COVID-19 drugs especially, small molecule inhibitors targeting the seminal proteins of viral etiological agent, SARS-CoV-2. MethodsBased on the traditional medicinal knowledge, we made an attempt through molecular docking analysis to explore the phytochemical constituents of three most commonly used Indian herbs in ‘steam inhalation therapy’ against well recognized viral receptor proteins. ResultsA total of 57 phytochemicals were scrutinized virtually against four structural protein targets of SARS-CoV-2 viz. 3CLpro, ACE-2, spike glycoprotein and RdRp. Providentially, two bioactives from each of the three plants i.e. apigenin-o-7-glucuronide and ellagic acid from Eucalyptus globulus; eudesmol and viridiflorene from Vitex negundo and; vasicolinone and anisotine from Justicia adhatoda were identified to be the best hit lead molecules based on interaction energies, conventional hydrogen bonding numbers and other non-covalent interactions. On comparison with the known SARS-CoV-2 protease inhibitor –lopinavir and RdRp inhibitor –remdesivir, apigenin-o-7-glucuronide was found to be a phenomenal inhibitor of both protease and polymerase, as it strongly interacts with their active sites and exhibited remarkably high binding affinity. Furthermore, in silico drug-likeness and ADMET prediction analyses clearly evidenced the usability of the identified bioactives to develop as drug against COVID-19. ConclusionOverall, the data of the present study exemplifies that the phytochemicals from selected traditional herbs having significance in steam inhalation therapy would be promising in combating COVID-19.

Quantitative structure-activity relationship, molecular docking, drug-likeness, and pharmacokinetic studies of some non-small cell lung cancer therapeutic agents

BackgroundLung cancer has been reported to be among the leading cancer cases in the world. It was also reported to have caused a lot of death every year and accounted for about one-third of the whole cancer deaths in the globe. The main subset of lung cancers that accounts for about 85% of the problems of lung cancer raised above was non-small cell lung cancer (NSCLC). The most common cause of NSCLCs that mostly affects women and cigarette smokers was recognized to be overexpression of epidermal growth factor receptor tyrosine kinase (EGFR TK).ResultsFive models on thirty five (35) NSCLC therapeutic agents were developed via quantitative structure-activity relationship (QSAR) technique. The best model among them was selected and reported due to its fitness statistically with the following validation parameters: R2 of 0.8764, R2adj of 0.8370, Qcv2 of 0.7655, R2test of 0.7024, and LOF of 0.3312. Molecular docking was used to elucidate the mode of binding interactions between the thirty five (35) NSCLC therapeutic agents and the binding pose of EGFR tyrosine kinase receptor (3IKA) in this research. Compound 29 was recognized to have the most excellent binding affinity of − 8.8 kcal/mol among others. The drug-likeness and pharmacokinetic properties of all the NSCLC therapeutic agents were predicted using SWISSADME, and none among the molecules under investigation violated more than the permissible limit of the conditions stated by Lipinski’s RO5 filters. Five hit compounds were identified using molecular docking virtual screening. The five (5) hit compounds were further screened and identified compound 16 and 27 as excellent among them using their pharmacokinetic profiles and drug-likeness properties.ConclusionQSAR technique was used to build five models on thirty five (35) NSCLC therapeutic agents. The best model among them was reported because it is statistically significant with good validation parameters. The molecular docking result has identified five (5) hit compounds. The most common amino acid residues to all hit compounds under investigation were Glu762, Leu718, Lys745, and Val726 which might be responsible for the higher inhibitory activities/binding affinities of the compounds under investigation. Furthermore, these five (5) hit compounds were further subjected to drug-likeness and pharmacokinetic properties prediction to determine which among them have the best pharmacokinetic profile. Compounds 16 and 27 among the hit compounds were observed to have high chance of passive absorption by the gastrointestinal tract while the other three have low tendency of passive absorption. More so, only compounds 16 and 27 have higher bioavailability scores, and none of the two have more than one violation of the RO5 criteria. The cause of efficiency of compounds 16 and 27 might be as a result of good pharmacokinetic profiles and drug-likeness properties possessed by the molecules when compared to other hit compounds.

Molecular docking studies of phytocompounds of Rheum emodi Wall with proteins responsible for antibiotic resistance in bacterial and fungal pathogens: in silico approach to enhance the bio-availability of antibiotics

Rheum emodi Wall. (Himalayan rhubarb) has many pharmacological activities such as antioxidant, antimicrobial, antiviral, anticancer and wound healing. The present study was aimed to understand if major phytocompounds of Rheum emodi could bind proteins responsible for antibiotic resistance in bacterial and fungal pathogens and enhance the potency of antibiotics. The major phytocompounds of R. emodi (emodin, rhein-13c6 and chrysophenol dimethy ether) were retrieved from the Pubchem and target proteins were retrieved from RCSB protein data bank. The docking study was performed by using AutoDock vina software and Molinspiration, swiss ADME servers were used for the determination of Lipinski rule of 5, drug-likeness prediction respectively, whereas, admetSAR and Protox-II tools were used for toxicity prediction. To study the docking accuracy of protein-ligand complexes, MD simulation for 100 ns was done by using Desmond program version 2.0 (Academic version). Among all the selected phytocompounds, emodin showed the best binding affinity against bacterial (Penicillin binding protein 3, 3VSL and fungal target (cytochrome P450 14 alpha-sterol demethylase 1EA1) with binding energy −8.2 and −8.0 Kcal mol−1 respectively. Similarly, rhein-13C6 showed the best binding affinity against fungal target (n-myristoyl transferase 1IYL) with binding energy −8.0 Kcal mol−1 which is higher than antibacterial and antifungal antibiotics. All the selected phytocompounds also fulfill Lipinski rule, non-carcinogenic and non-cytotoxic in nature. These compounds also showed high LD50 value showing non-toxicity of these phytocompounds. MD simulation studies of phytocompounds (emodin and rhein-13C6) define the stability of protein-ligand complexes with in 100 ns time scale. Communicated by Freddie R. Salsbury

Synthesis of Novel Oxadiazole Derivatives, Molecular Properties Prediction and Molecular Docking Studies

In this work, synthesis of novel 1,3,4-oxadiazole derivatives were reported. Good molecular properties profile was predicted for the target compounds. In drug likeness prediction, compound 4b and 8b possess the highest score of 0.31 and 0.33, respectively. Since the compounds have good bioactivity scores as kinase inhibitor, possible interactions of compounds with VEGFR-2 kinase and probable binding conformations were evaluated by molecular docking. All compounds formed hydrogen bonding interactions with Asp1046 amino acid of key residues.

Spectroscopic investigations, quantum chemical calculations and molecular docking studies of Mangiferin - an anti-viral agent of H1N1 Influenza virus

Abstract Mangiferin (MFN) is an anti-viral agent of H1N1 influenza virus which was reported to inhibit H1N1 neuraminidase (NA) enzyme with IC50 value of 0.82 μM. The MFN molecule was optimized using DFT method employing 6-31G(d,p) and 6-311G(d,p) basis sets. The experimental FT-IR and FT-Raman were performed for MFN molecule and compared with theoretical value. The MEP, NBO, global and local reactivity descriptors were used to describe the reactivity, selectivity and stability of MFN molecule. The electronic properties like UV-Vis absorption spectra and HOMO-LUMO band gap energy values were computed through TD-DFT approach. The biological activity of lead molecule was examined with the help of drug-likeness and ADMET predictions. A molecular docking investigation was carried out to interpret the binding mode and intermolecular interactions of MFN molecule in the active site of H1N1 NA enzyme. MFN molecule exhibits good biological activity and the observed results are exempt to helpful in drug design.

In Silico Prediction Tool for Drug-likeness of Compounds based on Ligand Based Screening

Drug Likeness prediction is a time-consuming and tedious process. An in-vitro method the drug development takes a long time to come to market. The failure rate is also another one to think about in this method. There are many in-silico methods currently available and developing to help the drug discovery and development process. Many online tools are available for predicting and classifying a drug after analyzing the drug-likeness properties of compounds. But most tools have their advantages and disadvantages. In this study, a tool is developed to predict the drug-likeness of compounds given as input to this software. This may help the chemists in analyzing a compound before actually preparing a compound for the drug discovery process. The tool includes both descriptor-based calculation and fingerprint-based calculation of the particular compounds. The descriptor-calculation also includes a set of rules and filters like Lipinski’s rule, Ghose filter, Veber filter and BBB likeness. The previous studies proved that the fingerprint-based prediction is more accurate than descriptor-based prediction. So, in the current study, the drug-likeness prediction tool incorporated the molecular descriptors and fingerprint-based calculations based on five different fingerprint types. The current study incorporated five different machine learning algorithms for prediction of drug-likeness and selected the algorithm, which has a high accuracy rate. When a chemist inputs a particular compound in SMILES format, the drug-likeness prediction tool predicts whether the given candidate compound is drug or non-drug.

Molecular docking studies, drug-likeness and in-silico ADMET prediction of some novel β-Amino alcohol grafted 1,4,5-trisubstituted 1,2,3-triazoles derivatives as elevators of p53 protein levels

Malaria is a killer disease caused by Plasmodium falciparum and is responsible for over a million death annually. Chloroquine, quinine, pyrimethamine, proguanil, artemisinin, atovaquone, and mefloquine are different kinds of drugs employed to treat the disease, but due to increased drug resistance to these drugs, their use becomes less effective. Hence, the need for new antimalarial drugs with better activities and a new mechanism of action along different pathways against a new target. As well as the knowledge of their interactions, the drug-likeness of antimalarial drugs is necessary. Twenty-four derivatives of β-Amino alcohol grafted 1,4,5-trisubstituted 1,2,3-triazoles were docked against a p53 protein, as well as predicting their drug-likeness and ADMET properties. From the docking analysis, compound 10, {1-(1-benzyl-5-phenyl-1H-1,2,3-triazol-4-yl)-1-(4-bromophenyl)-2-((3,4-dimethylphenyl)amino)ethanol} was found to be the most stable compound with Re-rank docking score -100.295KJmol−1 against p53 protein. The “drug-likeness” and ADMET prediction performed nearly showed compliance with the Lipinski rule, and the compounds were found to have good absorption, distribution, metabolism, and excretion generally. The results of the study can be used for future optimization of derivatives of {1-(1-benzyl-5-phenyl-1H-1,2,3-triazol-4-yl)-1-(4-bromophenyl)-2-((3,4-dimethylphenyl)amino)ethanol}for better molecular interactions with p53 protein, and effective Plasmodium falciparum inhibition.