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Modern day sanjeevani has been proclaimed to be present in lesser explored regions of the Himalayas. In this research work out of the many possibilities of plants being touted as sanjeevani, Dendrobium plicatile has been explored for its medicinal as well as other properties using In-silico docking and modeling approaches. Use of various software and servers has yielded promising results indicating potential application of phytochemicals in Dendrobium plicatile as controllers against various ailments. Properties like water solubility, physiochemical characteristics, pharmacokinetics, drug likeness, medicinal properties and lipophilicity have been revealed using on-line SWISS-ADME server. The phytochemicals are also found to fulfill various criteria for being a suitable drug based on Lipinski filter. Moreover the possible targets of phytochemicals have been unraveled through Swiss Target Prediction server and interaction with targets proved using docking simulations performed using iGemDock server. The findings suggest multifarious targets as well as potential applications of phytochemicals. The fulfillment of various criteria is also indicative of future use of phytochemicals as drug molecules, hence proving the role as sanjeevani.

The World Health Organization (WHO) considers cancer as the deadliest disease, due to the increase in death in the 21 century. In the search for new therapeutic molecules, the scientific researches consider the proviral integration moloney (Pim) kinases as promising therapeutic targets for the treatment of hematological cancers. A series of thirty-four 3,5-disubstituted indole derivatives as potent Pim1 kinase inhibitors were studied using 3D-QSAR (CoMFA and CoMSIA) and molecular docking. CoMFA analysis showed Q2 value of 0.56, R2 value of 0.86 and rtest2 value of 0.78, while CoMSIA analysis showed a Q2 value of 0.73, R2 value of 0.93 and rtest2 value of 0.80. The models were generated using 28 compounds as training set and 6 compounds as test set. Furthermore, the contour maps acquired from the CoMSIA and CoMFA models were used to rationalize the principal structural requirement responsible for the activity. As results, four new compounds were designed in silico. Furthermore, the newly designed compound X1 and the most active compound 28 were subjected to molecular docking study in order to validate their stability. Molecule docking shows that compound X1 has greater stability than compound 28. The newly compounds were evaluated for in silico toxicity properties and verified the five Lipinski rules for wet-lab applicability.

A forty-two compounds series of potential epidermal growth factor receptor kinase inhibitors of Pyrazole derivatives containing thiourea analogs have been subjected to 3D-QSAR (3-Dimensional Quantitative Structural-Activity Relationship) studies using CoMFA (Comparative Molecular Field Analysis) and CoMSIA (Comparative Molecular Similarity Indices Analysis). The training set and the test set of pyrazole derivatives have been used for the generation and validation of QSAR model, respectively. Dataset alignment has been performed using the lowest energy conformer of the most active compound. The best-generated CoMFA and CoMSIA models exhibit conventional determination coefficients R2 of 0.982 and 0.980 as well as the Leave One Out cross validation determination coefficients Q2 of 0.734 and 0.801, respectively. Moreover, the predictive ability of those models was evaluated by the external validation using a test set of five compounds with predicted determination coefficients R2test of 0.932 and 0.846, respectively. Based on those satisfactory results, ten new compounds have been designed and predicted by in silico Drug likeness and ADMET method. In addition, molecular docking studies were carried out to explore the binding interactions of the selected compounds with the enzyme. This study could expand the understanding of pyrazole derivatives as anti-cancer agent and would be of great help in lead optimization for early drug discovery of highly potent anticancer activity.

The drug-likeness of a compound is a key factor during the initial phases of drug discovery. It can be defined as the similarity between compounds and drugs. Here, we collate research related to the fraction of sp3 carbon atoms (Fsp3), including related high-throughput screening (HTS) cases, structural modifications based on Fsp3, and strategies to improve it. We also introduce new synthetic methods for spirocyclic scaffolds. It is likely that the reasonable rigidity of spirocyclic scaffolds will provide a new generation of drug candidates.

Quantitative structure-activity relationships and drug-likeness evaluations were investigated for 33 compounds of 1,2-diazole derivatives as anti-mycobacterium tuberculosis. MLR procedures were used to obtain QSAR models. The predictivity of the models was estimated using cross-validation with the leave-one-out method. The results show a high correlation between the experimental and predicted activity values, indicating the good quality of the QSAR model.

Undesirable pharmacokinetic (PK) properties or unacceptable toxicity are the main causes of the failure of drug candidates at the clinical trial stage. Since the concept of drug-likeness was first proposed, it has become an important consideration in the selection of compounds with desirable bioavailability during the early phases of drug discovery. Over the past decade, online resources have effectively facilitated drug-likeness studies in an economical and time-efficient manner. Here, we provide a comprehensive summary and comparison of current accessible online resources, in terms of their key features, application fields, and performance for in silico drug-likeness studies. We hope that the assembled toolbox will provide useful guidance to facilitate future in silico drug-likeness research.

Virtual screening emerged as an important tool in our quest to access successful CNS medicaments for treating Alzheimer's disease. The computational techniques applied in this screening are central nervous system multiparameter optimization (CNS MPO), golden triangle rule, structure activity/property relationships (SAR/SPR), Drug-likeness properties, and lipophilicity indices. These techniques offer the ability to guide drug design and selection to a quickly identify the compounds from a class of acetylcholinesterase inhibitors being pyridazine derivatives, with desirable drug-like attributes.

In spite of therapeutic development against life threatening fungal pathogens like Candida albicans, the repertoire of effective antifungal drugs is lagging. The emergence and persistence of azole/echinocandin resistance and other cases of multi-drug resistance have led to the failure of the antifungal treatment regime. This troublesome scenario has steered a need for the development of novel leads. Computer aided in-silico drug design using virtual screening, molecular docking, drug likeness, absorption, distribution, metabolism, excretion, and toxicity analysis for the identification of lead compounds for further in-vitro analysis is a cost effective and time-saving strategy. The present study used these strategies to discover novel lead antifungal from the pool of second largest occurring natural compound lignin. After the virtual screening of lignin derivatives, Sodium lignosulfonate (LIG) was identified as the best lead for further analysis. After this vigorous in-silico analysis, LIG was then tested in-vitro against 5 different Candida species. MIC value of LIG against Candida spp. was found to be 64-128μg/ml. The study is revealing LIG as a potent and persuasive antifungal agent. In the race of Candida therapeutics, the revelation of the antifungal potential of such natural compounds might impact and diversify the discovery and development of novel antifungal agent.

Optimized geometry and vibrational wave numbers of the normal modes of Benzoguanamine (BG) have been investigated using Gaussian’09 at B1B95/6–31 G (d) level. Present work elucidates structural and spectral analysis of the title compound. Redistribution of electron density (ED) in various bonding and antibonding orbitals along with E(2) energies have been calculated by natural bond orbital (NBO) analysis to give clear evidence of stabilization originating from the hyper conjugation of various intra-molecular interactions. HOMO-LUMO analysis has been performed to analyze charge transfer interactions within the molecule. The chemical implication of the molecule was explained using ELF, LOL with contour maps. Molecular docking was performed with various target proteins inorder to confirm the biological activity of compound and drug likeness influences were designed to realize the biological assets of BG.

Graphical abstract, In this work novel antiviral compound 4-(Dimethylamino) Pyridinium 3, 5-dichlorosalicylate was synthesized and characterized by UV–vis, FT-IR, FT-Raman, 1H NMR and 13C NMR spectra. Quantum chemical computations were carried out by Density functional theory methods at B3LYP level. Electronic stability of the compound arising from hyper conjugative interactions and charge delocalization is investigated using natural bond orbital analysis. Assignments of vibrational spectra have been carried out with the aid of Normal coordinate analysis following the SQMFF methodology. TD-DFT approach was applied to assign the electronic transition observed in UV visible spectrum measured experimentally. Frontier molecular orbital energy gap affirms the bioactivity of the molecule and NCI analysis gives information about inter and intra non covalent interactions. ESP recognises the nucleophilic and electrophilic regions of molecule and the chemical implication of molecule was explained using ELF, LOL. The reactive sites of the compound were studied from the Fukui function calculations and chemical descriptors define the reactivity of the molecule. Molecular docking done with SARS and MERS proteins endorses the bioactivity of molecule and drug likeness factors were calculated to comprehend the biological assets of DADS.

Enormous efforts have been made in the past to identify novel scaffolds against the potential therapeutic target, Plasmodium falciparum dihydroorotate dehydrogenase (PfDHODH). Fourteen different organic molecules have been crystallized to understand the structural basis of the inhibition. However, the pharmacophoric studies carried out so far, have not exploited all the structural information simultaneously to identify the novel inhibitors. Therefore, an attempt was made to construct the pharmacophore hypotheses from the available PfDHODH structural proteome. Among the generated hypotheses, a representative hypothesis was employed as a primary filter to list the molecules with complimentary features accountable for inhibition. Moreover, the auxiliary evaluations of the filtered molecules were accomplished via docking and drug-likeness studies. Subsequently, the stability of the protein-ligand complex was evaluated by using molecular dynamics simulations (MDs). The molecular details of binding interactions of the potential hits were compared with the highly active experimental structure (5FI8) to seek the more potent candidates that can be targeted against PfDHODH. Overall, the combination of screening and stability procedures resulted in the identification of three potent candidates. The drug-likeness of these molecules lie within the acceptable range and consequently increased the opportunities for their development to new anti-malarials.

Display Omitted Efficiency indices and pose clustering was used for effective decision making.Method was validated by experimental SARs.As an example 720 furanones were docked against Pf-DHFR binding site.Scaffold class I (Indandione derived) performed better in efficiency plane.Introduction of polarity in isocyanide decreased the drug likeness of furanones. In the present report, the role of computationally estimated efficiency indices and pose clustering has been demonstrated in effective decision making, resource management and chemical prioritization. As an example, 720 annulated furanones from six different scaffold classes were computationally docked against Pf-DHFR active site using AutoDock 4.2. Many trends were established by navigating efficiency indices (BEI and SEI) in 2D planes. These trends were then explained by comparing interaction profiles of docked poses with that of known actives/inhibitors. Cases where trends emerged from efficiency plots resonated well with the pattern of a particular cluster diagram were considered as guidelines for optimization purpose. These kind of guidelines can help medicinal chemists in prioritization their work and in effective management of time, energy and chemical resources.

Recently, macroalgae or seaweeds serve as a treasure of potential drugs for cancer therapy. The present study investigated the cytotoxic activity of eight compounds isolated from the brown alga Sargassum platycarpum for the first time. These isolates were identified as hexadecanoic acid (1), oleic acid (2), saringosterol (3 and 4, 1:1 mixture of C-24epimers), β-sitosterol (5), glycoglycerolipid (6), loliolide (7) and Kjellmanianone (8) by spectroscopic techniques. Two epimers of saringosterol, (24-R)-saringosterol (3) and (24-S)-saringosterol (4), were subsequently separated by HPLC. (24-S)-saringosterol (4) and (24-R)-saringosterol (3) exhibited potent cytotoxicity against HepG-2 cells with IC50 of 0.10±0.00 and 0.11±0.00 µM, respectively with compared to standard 5-Fluorouracil (IC50 of 0.63±0.28 µM) and other isolates. MEP, EHOMO, ELUMO and global properties of all isolated compounds are computed by DFT methods. Molecular docking study showed that most of the isolated compounds especially compounds 3 and 4 interact strongly with 4PYP with the highest binding energies maintained that the high cytotoxic activity of these compounds against HepG-2 cells in the experimental part. Bioactivity Score, Drug-Likeness and ADMET studies supported the potential biological activities of most isolated compounds especially compounds 3 and 4 and also created attention for developing them to act as good candidates.

The rule of 5 methodology appears to be as useful today in defining drugability as when it was proposed, but recognizing that the database that we used includes only drugs that successfully reached the market. We do not view additional criteria necessary nor did we find significant deficiencies in the four Rule of 5 criteria originally proposed by Lipinski and coworkers. BDDCS builds upon the Rule of 5 and can quite successfully predict drug disposition characteristics for drugs both meeting and not meeting Rule of 5 criteria. More recent expansions of classification systems have been proposed and do provide useful qualitative and quantitative predictions for clearance relationships. However, the broad range of applicability of BDDCS beyond just clearance predictions gives a great deal of further usefulness for the combined Rule of 5/BDDCS system.

A series of new edaravone derivatives 3-7 have been synthesized, characterised using various spectroscopic techniques and screened for their in vitro anti-cancer, antioxidant activities. Structure of 5d was further substantiated through single crystal X-ray diffraction. Among the tested, 5l exhibited pronounced activity against PC3 cancer cells. Compounds 5i, 5l, 7c showed potent activity against A549 cancer cells. Products 5k, 6, 7c demonstrated good antioxidant activity with MIC values of 18.60, 16.27, 16.07μg/mL respectively. Further the reported analogues were also tested on normal HEK293T cells and displayed low to good safer profiles. Derivatives 5l and 7c have come out to be safer potent anticancer, antioxidant agents. Additionally, the target products were subjected to their molecular properties prediction and drug likeness by employing Molinspiration and Osiris property explorer toolkits. None of them violated Lipinski's boundaries classifying the title compounds as potential anticancer and antioxidant agents.

Tuberculosis, an infectious disease, has been reported to cause the death of 1.5 million in 2018. Due to the emergence of Multi-Drug Resistant-TB, Extensively Drug Resistant-TB, and Totally Drug Resistant-TB, many first-line and second-line drugs have been found in-effective. New drugs introduced in TB regimens such as pretomanid, bedaquiline and linezolid have been associated with toxicities. Hence, there is an urgent need for introducing safe and cost-effective antitubercular drugs. In this study, a series of Schiff bases of 2-amino thiazoles were synthesized and evaluated for their anti-tubercular activity against Mycobacterium tuberculosis H37Rv strain by Microplate Alamar Blue assay (MABA) method. N-[4-(2-Amino-thiazol-4-yl)-phenyl]-benzamide derivative with 2-nitro (5c2), 4-hydroxy (5c4) substitution, 2-[4-(2-Amino-thiazol-4-yl)-phenyl]-isoindole-1,3-dione derivatives with 3,4,5-trimethoxy substitution (5b1) and the compound 1-[4-(2-Amino-thiazol-4-yl)-phenyl]-pyrrole-2,5-dione (4a) which is a maleic derivative bearing thiazole ring, exhibited good anti-tubercular activity (MIC 6.25 μg/ml). Drug likeness was also evaluated for all the synthesised compounds using Molinspiration software. All synthesized compounds fulfilled the parameters of the Lipinski rule of five and showed drug-like properties. Through this study, it was proved that thiazole analogues have good anti-tubercular potentials.

Warburgia ugandensis Sprague is an endemic plant to Africa and widely distributed in lower rain forests and drier highland forests of Kenya, Uganda and Ethiopia. In south eastern part of Ethiopia (Bale) W. ugandensis is known as Befti and widely used as traditional medicine for the treatment of various diseases such as asthma, cough, diarrhea, common cold, stomachache and toothache. It is also used to remove tapeworm. Phytochemical investigation on the n-hexane and dichloromethane extracts of the stem bark of this plant afforded two sesquiterpenes; namely, HP-66 (Nerolidol) and HP-79 (Muzigadial). The structural elucidations of these compounds were accomplished by using a variety of spectroscopic methods (IR, UV and NMR). The spectroscopic results compared with the reported data in the literature. HP-66 (Nerolidol) was reported from Warburgia ugandensis Sprague for the first time. Parameters drug-likeness and physicochemical properties including pharmacokinetics analysis of the HP-66 (Nerolidol) and HP-79 (Muzigadial) compounds was performed using online tool Swiss ADME.

COV spike (S) glycoprotein and Mpro are two key targets that have been identified for vaccines and drug development against the COVID-19 disease. Virtual screening of some compounds of plants origin that have shown antiviral activities were carried out on the two targets, 6lu7 and 6vsb by docking with the PyRx software. The binding affinities were compared with other compounds and drugs already identified as potential ligands for 6lu7 and 6vsb as well as Chloroquine and hydroxychloroquine. The docked compounds with best binding affinities were also filtered for drug likeness using the SwissADME and PROTOX platforms on the basis of Physicochemical properties and toxicity respectively. The docking results revealed that scopodulcic acid and dammarenolic acid had the best binding affinity on the s-glycoprotein and Mpro protein targets respectively. Silybinin also demonstrated a good binding affinity to both protein targets making it a potential candidate for further evaluation as repurposed candidate for SARS COV2 with likelihood of having a multitarget activity.

Understanding the relationships between drugs and symptoms has broad medical consequences, yet a comprehensive description of the drug-symptom associations is currently lacking. Here, 1441 FDA-approved drugs were collected, and PCA was used to extract 122 descriptors which explained 91% of the variance. Then, a k-means++ method was employed to partition the drug dataset into 3 clusters, and 3 corresponding SVDD models (drug-likeness screening models) were constructed with an overall accuracy of up to 95.6%. Furthermore, 6878 herbal molecules from the TcmSP™ database were screened by the above 3 SVDD model to obtain 5309 candidate drug molecules with highly accept classification of 77.19%. To assess the accuracy of the SVDD models, 8559 herbal molecule-symptom co-occurrences were mined from Pubmed abstracts, involving 697 herbal molecules and 314 symptoms. Most of the 697 herbal molecules could be found in the accepted SVDD data (5309 molecules), showing the potential of the SVDD for the screening of drug candidates. Moreover, a herbal molecule-herbal molecule network and a herbal molecule-symptom were constructed. Overall, the results provided a new drug-likeness screening approach independent to abnormal training data, and the comprehensive collection of herbal molecule-symptom associations formed a new data resource for systematic characterization of the symptom-oriented medicines.

The concept of drug-likeness, established from the analyses of the physiochemical properties or/and structural features of existing small organic drugs or/and drug candidates, has been widely used to filter out compounds with undesirable properties, especially poor ADMET (absorption, distribution, metabolism, excretion, and toxicity) profiles. Here, we summarize various approaches for drug-likeness evaluations, including simple rules/filters based on molecular properties/structures and quantitative prediction models based on sophisticated machine learning methods, and provide a comprehensive review of recent advances in this field. Moreover, the strengths and weaknesses of these approaches are briefly outlined. Finally, the drug-likeness analyses of natural products and traditional Chinese medicines (TCM) are discussed.

Objective To identify alternative drug for the treatment of pandemic disease caused by influenza virus. Methods The structure based drug design approach was employed. New sequence was employed to build the N1 simulation structure by homology modeling which was further checked for high reliability by verify score and Ramachandran plot. Evaluation of drug likeness and absorption, distribution, metabolism, excretion, toxicity showed that the ligands satisfy all the properties to be used as a drug. Docking studies were performed using LeadIT and docking scores indicated good binding energy values towards N1. Results Four candidates were screened and suggested as potent target candidates from the docking studies. The screened compounds from Stemonaceae family illustrated better activity compared to the drugs which are already present in the market. Conclusions The results may help to find the alternative drug to solve the drug-resistant problem and stimulate designing more effective drugs against 2009-H1N1 influenza pandemic, yet pharmacological studies have to confirm it.

Several hH 3 R antagonists/inverse agonists entered clinical phases for a broad spectrum of mainly centrally occurring diseases. Nevertheless, many promising candidates failed due to their pharmacokinetic profile, mostly because of their strong lipophilicity and their dibasic character. Analysis of previously, as potential PET ligands synthesized compounds (ST-889, ST-928) revealed promising results concerning physicochemical properties and drug-likeness. Herein, the synthesis, the evaluation of the binding properties at the hH 3 R and the estimation of different physicochemical and drug-likeness properties of further novel benzylpiperidine variations on H 3 R antagonists is described. Due to the introduction of various small hydrophilic moieties in the structure, drug-likeness parameters have been improved. For instance, compound 12 (ST-1032) showed in addition to high affinity at the H 3 R (p K i (hH 3 R) = 9.3) c log S , c log P , LE, LipE, and LELP values of −2.48, 2.18, 0.44, 7.14, and 4.95, respectively. Also, the keto derivative 5 (ST-1703, p K i (hH 3 R) = 8.6) revealed LipE and LELP values of 5.25 and 6.84, respectively.

Introduction In clinical practice, Nao An Capsule (NAC), a traditional Chinese medicine (TCM) prescription, is regarded as having good therapeutic effect on ischemic stroke (IS). A network pharmacology based method was used to uncover the active substances and mechanism of NAC in treatment of IS. Methods The components of NAC, in addition to their interacting targets, were searched from the TCMSP database. The components were filtered by the metrics of oral bioavailability and drug likeness, and the targets were compared to the disease associated ones searched from the CTD and TTD databases. After that, the components and targets were fed into the Cytoscape software to build a component-target-disease network. Afterwards, the protein-protein interactions among the identical targets were visualized by the STRING database, and the GO and pathway enrichment analysis were performed by the Metascape database. Finally, the potential active substances and targets were validated by molecular docking simulation. Results 51 compounds, 325 interacting targets in addition to 54 disease-related targets were obtained, in which 16 identical targets were observed, and analyzed to be enriched in 18 pathways. 13 of those identical targets had compact relationships with each other in STRING analysis. The compounds interacting with the 13 targets had stronger affinities than the native ligands in molecular docking simulation. Conclusion The present method did not only preliminarily reveal the active substances and mechanism of NAC in treatment of IS from the perspective of network pharmacology, but show its potential application for research and development of other TCM prescriptions.

A series of N,5-disubstituted-1,3-thiazolidine-2,4-dione analogues (3a–h, 4a–h) were prepared by knoevenagel condensation of various aromatic aldehydes with N-substituted-1,3-thiazolidine-2,4-diones in toluene. The structures of the synthesized compounds were established based on the IR, 1H NMR, Mass and elemental analysis data. Drug likeness of the synthesized molecules were evaluated using online Molinspiration web JME Editor and OSIRIS Property Explorer and were found to obey rule of thumb.

Hetrocyclic 1, 5-benzothiazepines compounds were synthesized and screened for drug likeness property using Lipinski's rule of five. Among 20 compounds of benzothiazepine three compounds were further evaluated for the conformation based molecular docking studies using lib dock. The crucial amino acids of MAP kinase are MET109, LYS53, TYR35, THR106, ALA51 the binding of compounds with active site amino acid will show specific inhibition with MAP kinase protein. The BTZ-6b, BTZ-16 and BTZ-17 shows the specific binding with active site amino acid residues of TYR35, LYS53 specifically and the other amino acid present in the active shows Vanderwaals interaction with protein with good dock score.

Natural products currently represent an underutilized source of leads for the pharmaceutical industry, especially when one considers that almost 50% of all drugs were either derived from such sources or are very closely related. Lamellarins are a class of natural products with diverse biological activities and have entered into preclinical development for the treatment of multidrug-resistant tumors. Although these compounds demonstrated good cell penetration, as observed by their low μM activity in whole cell models, they have not been extensively profiled from a physicochemical point of view, and this is the goal of this study. For this study, we have determined the experimental logP values of a set of 25 lamellarins, given it is the single most important parameter in determining multiple ADMET parameters. We also discuss the relationship between this natural product class, natural product derivatives in development and on the market, oral marketed drugs, as well as drug molecules in development, using a range of physicochemical parameters in conjunction with principal components analysis (PCA). The impact of this systematic analysis on our ongoing medicinal chemistry strategy is also discussed.

High performance liquid chromatographic (HPLC) method has been developed to separate the members of a library including 24 benzylidenecycloalkanone-type structures and to characterize their lipophilicity. The experimental lipophilicity data (k) of the compounds have been compared with their calculated lipophilicity parameters (CLOGP). In general, good correlations between the measured and calculated lipophilicities have been found and these results were in good accordance with our previously data obtained in case of structurally related molecular libraries. In addition, cytotoxicity screening has been performed to determine the antiproliferative activity of these compounds. Some of the investigated compounds possessed noticeable inhibitory potential. Based on the correlation between the antiproliferative activity and experimentally determined lipophilicity of the molecules investigated, limited structural demands to obtain more potent compounds can be exhibited to support the synthetic design.

Novel analytic methods are required to assimilate the large volumes of structural and bioassay data generated by combinatorial chemistry and high-throughput screening programmes in the pharmaceutical and agrochemical industries. This paper reviews recent work in visualisation and data mining that can be used to develop structure-activity relationships from such chemical/biological datasets.