Mapping the binding site of the nucleoside transporter protein: a 3D-OSAR study

Exploring nature's bounty: identification of Withania somnifera as a promising source of therapeutic agents against COVID-19 by virtual screening and in silico evaluation

Coronaviruses are etiological agents of extreme human and animal infection resulting in abnormalities primarily in the respiratory tract. Presently, there is no defined COVID-19 intervention and clinical trials of prospective therapeutic agents are still in the nascent stage. Withania somnifera (L.) Dunal (WS), is an important medicinal plant in Ayurveda. The present study aimed to evaluate the antiviral potential of selected WS phytoconstituents against the novel SARS-CoV-2 target proteins and human ACE2 receptor using in silico methods. Most of the phytoconstituents displayed good absorption and transport kinetics and were also found to display no associated mutagenic or adverse effect(s). Molecular docking analyses revealed that most of the WS phytoconstituents exhibited potent binding to human ACE2 receptor, SAR-CoV and SARS-CoV-2 spike glycoproteins as well as the two main SARS-CoV-2 proteases. Most of the phytoconstituents were predicted to undergo Phase-I metabolism prior to excretion. All phytoconstituents had favorable bioactivity scores with respect to various receptor proteins and target enzymes. SAR analysis revealed that the number of oxygen atoms in the withanolide backbone and structural rearrangements were crucial for effective binding. Molecular simulation analyses of SARS-CoV-2 spike protein and papain-like protease with Withanolides A and B, respectively, displayed a stability profile at 300 K and constant RMSDs of protein side chains and Cα atoms throughout the simulation run time. In a nutshell, WS phytoconstituents warrant further investigations in vitro and in vivo to unravel their molecular mechanism(s) and modes of action for their future development as novel antiviral agents against COVID-19.

Computer-aided drug design and virtual screening of targeted combinatorial libraries of mixed-ligand transition metal complexes of 2-butanone thiosemicarbazone

The present paper deals with in silico evaluation of 32 virtually designed transition metal complexes of 2-butanone thiosemicarbazone and N,S,O containing donor hetero-ligands namely py, bpy, furan, thiophene, 2-picoline, 1,10-phenanthroline, piperazine and liquid ammonia. The complexes were designed with a view to assess their potential anticancer, antioxidant and antibacterial activity. The absorption, distribution, metabolism, excretion and toxicity (ADMET) properties of the chosen ligands were calculated by admetSAR software. Metabolic sites of different ligands likely to undergo metabolism were predicted using Metaprint 2D. The proposed complexes were also evaluated for their drug-like quality based on Lipinski's, Veber, Ghose and leadlikeness filters. Druglikeness and toxicity potential were predicted by OSIRIS property explorer. The pharmacokinetic properties and bioactivity scores were calculated by Molinspiration tool. Bioactivity scores of the complexes were predicted for drug targets including enzymes, nuclear receptors, kinase inhibitors, G-protein coupled receptor ligands and ion channel modulators. Molecular docking of selected Fe(II) mixed-ligand complexes was performed using AutoDock version 4.2.6 and i-GEMDOCK version 2.1 with two target proteins namely Ribonucleotide reductase (RR) and Topoisomerase II (Topo II). The results were compared with three standard reference drugs viz. Doxorubicin HCl, Letrozole (anticancer) and Tetracycline (antibiotic). Multivariate data obtained were analyzed using principal component analysis (PCA) for visualization and projection as scatter and 3D plots. Positive results obtained for hetero-ligands using admetSAR version 1.0 indicated good absorption and transport kinetics of the hetero-ligand complexes through the human intestine and blood-brain barrier. The hetero-ligands were predicted to have no associated mutagenic effect(s) also. However, none of the hetero-ligands was predicted to be Caco-2 (human colon cancer cell line) permeable. Most of the hetero-ligands and the parent ligand (2-butanone thiosemicarbazone) were predicted to undergo Phase-I metabolism prior to excretion using MetaPrint2D software. Pharmacokinetic evaluation of the proposed complexes revealed that all complexes displayed drug-like character and were predicted to have no apparent toxic side-effects. All the proposed complexes showed moderate to good biological activity scores (-5.0 to 0.0). Mixed complexes with bpy, 2-picoline and 1,10-phenanthroline showed significant bioactivity scores (as enzyme inhibitors) in the range 0.02-0.13. Likewise, good docking scores were obtained for Fe (II) complexes with the same ligands. [FeL(2-pic)₂] displayed the lowest binding energy (-6.47 kcal/mol) with respect to Topo II followed by [FeL(py)₂] (-6.14 kcal/mol) as calculated by AutoDock version 4.2.6. With respect to binding with RR, [FeL(2--pic)₂] again displayed the lowest binding energy (-7.21 kcal/mol) followed by [FeL(py)₂] (-5.96 kcal/mol). On the basis of docking predictions and various other computational evaluations, four mixed-ligand complexes of Fe in +2 oxidation state with py, bpy, 2--picoline and 1,10-phenanthroline were synthesized with 2-butanone thiosemicarbazone. All the synthesized Fe complexes were characterized using various spectroscopic techniques and tested for their potential anticancer activity in vitro against human breast carcinoma cell line MDA-MB 231 and human lung carcinoma cell line A549 cell line using MTT assay. [FeL(2-pic)₂], [FeL(bpy)], and [FeL(py)₂] were found to exhibit significant antiproliferative activity with IC₅₀ values in the range of 80-100 μM against breast and lung cancer cells. The synthesized Fe complexes also displayed mild antioxidant activities. The synthesized and studied Fe complexes have the potential for development into future anticancer agents if analyzed and modified further for improvement of their ADMET, solubility and permeability criteria set for potential drug-candidates.

Exploring the novel heterocyclic derivatives as lead molecules for design and development of potent anticancer agents

This paper deals with in silico evaluation of newly proposed heterocyclic derivatives in search of potential anticancer activity. Best possible drug candidates have been proposed using a rational approach employing a pipeline of computational techniques namely MetaPrint2D prediction, molinspiration, cheminformatics, Osiris Data warrior, AutoDock and iGEMDOCK. Lazar toxicity prediction, AdmetSAR predictions, and targeted docking studies were also performed. 27 heterocyclic derivatives were selected for bioactivity prediction and drug likeness score on the basis of Lipinski's rule, Viber rule, Ghose filter, leadlikeness and Pan Assay Interference Compounds (PAINS) rule. Bufuralol, Sunitinib, and Doxorubicin were selected as reference standard drug for the comparison of molecular descriptors and docking. Bufuralol is a known non-selective adreno-receptor blocking agent. Studies showed that beta blockers are also used against different types of cancers. Sunitinib is well known Food and Drug administration (FDA) approved pyrrole containing tyrosine kinase inhibitor and our proposed molecules possess similarities with both drug and doxorubicin is another moiety having anticancer activity. All heterocyclic derivatives were found to obey the drug filters except standard drug Doxorubicin. Bioactivity score of the compounds was predicted for drug targets including enzymes, nuclear receptors, kinase inhibitors, G protein-coupled receptor (GPCR) ligands and ion channel modulators. Absorption, distribution, metabolism and toxicity (ADMET) prediction of all proposed compound showed good Blood-brain barrier (BBB) penetration, Human intestinal absorption (HIA), Caco-2 cell permeability except compound-11 and was found to have no AdmetSAR toxicity as well as carcinogenic effect. Compounds 1-9 were slightly mutagenic while compound 2, 11, 20 and 21 showed carcinogenic effect according to Lazar toxicity prediction. Rests of the compounds were predicted to have no side effect. Molecular docking was performed with vascular endothelial growth factor receptor-2(VEGFR2) and glutathione S-transferase-1 (GSTP1) because both are common cancer causing proteins. Sunitinib and Doxorubicin possess great affinity to inhibit these cancers causing protein. Self-organizing map (SOM) was used to depict data in a simple 2D presentation. Our studies justify that good oral bioavailability and therapeutic efficacy of 10, 12-19 and 22-27 compounds can be considered as potential anticancer agents.

Antiprotozoal Nitazoxanide Derivatives: Synthesis, Bioassays and QSAR Study Combined with Docking for Mechanistic Insight

In view of the serious health problems concerning infectious diseases in heavily populated areas, we followed the strategy of lead compound diversification to evaluate the near-by chemical space for new organic compounds. To this end, twenty derivatives of nitazoxanide (NTZ) were synthesized and tested for activity against Entamoeba histolytica parasites. To ensure drug-likeliness and activity relatedness of the new compounds, the synthetic work was assisted by a quantitative structure-activity relationships study (QSAR). Many of the inherent downsides – well-known to QSAR practitioners – we circumvented thanks to workarounds which we proposed in prior QSAR publication. To gain further mechanistic insight on a molecular level, ligand-enzyme docking simulations were carried out since NTZ is known to inhibit the protozoal pyruvate ferredoxin oxidoreductase (PFOR) enzyme as its biomolecular target.

Atom type preferences, structural diversity, and property profiles of known drugs, leads, and nondrugs: a comparative assessment

A new characterization of known drug, lead, and representative nondrug databases was performed taking into account several properties at the atomic and molecular levels. This characterization included atom type preferences, intrinsic structural diversity (Atom Type Diversity, ATD), and other well-known physicochemical properties, as an approach for rapid assessment of druglikeness for small molecule libraries. To characterize ATD, an elaborate united atom classification, UALOGP (United Atom Log P), with 148 atom types, was developed along with associated atomic physicochemical parameters. This classification also enabled an analysis of atom type and physicochemical property distributions (for calculated log P, molar refractivity, molecular weight, total atom count, and ATD) of drug, lead, and nondrug databases, a reassessment of the Ro5 (Rule of Five) and GVW (Ghose−Viswanadhan−Wendoloski) criteria, and development of new criteria and ranges more accurately reflecting the chemical space occupied by small molecule drugs. A relative druglikeness parameter was defined for atom types in drugs, identifying the most preferred types. The present work demonstrates that drug molecules are constitutionally more diverse relative to nondrugs, while being less diverse than leads.

Molecular requirements of the human nucleoside transporters hCNT1, hCNT2, and hENT1

Concentrative nucleoside transporters (CNTs) and equilibrative nucleoside transporters (ENTs) are important in physiological and pharmacological activity and disposition of nucleosides and nucleoside drugs. A better understanding of the structural requirements of inhibitors for these transporters will aid in designing therapeutic agents. To define the relative and unified structural requirements of nucleoside analogs for interaction with hCNT1, hCNT2, and hENT1, we applied an array of structure-activity techniques. Unique pharmacophore models for each respective nucleoside transporter were generated. These models reveal that hCNT2 affinity is dominated by hydrogen bonding features, whereas hCNT1 and hENT1 displayed mainly electrostatic and steric features. Hydrogen bond formation over 3'-OH is essential for all nucleoside transporters. Inhibition of nucleoside transporters by a series of uridine and adenosine analogs and a variety of drugs was analyzed by comparative molecular field analysis. Cross-validated r2 (q2) values were 0.65, 0.52, and 0.74 for hCNT1, hCNT2, and hENT1, respectively. The predictive quality of the models was further validated by successful prediction of the inhibition of a set of test compounds. Addition of a hydroxyl group around the 2-position of purine (or 3-position of pyrimidine) may increase inhibition to hCNT2 transporter; addition of hydroxyl group around the 2,7-position of purine (or the 3,5-position of pyrimidine) would increase the inhibition to hENT1 transporter. Utilization of these models should assist the design of high-affinity nucleoside transporter inhibitors and substrates for both anticancer and antiviral therapy.

Synthesis, molecular modeling and QSAR studies in chiral 2,3-disubstituted-1,2,3,4-tetrahydro-9H-pyrido(3,4-b)indoles as potential modulators of opioid antinociception

In view of coexistence of opioid and cholecystokinin (CCK) in the brain areas concerned with pain processing, some semirigid racemic and chiral analogues of a potent CCK receptor antagonist (benzotript) have been synthesized and tested for their modulatory role on opioid antinociception, which may be mediated by CCK-B receptor. Some of these compounds, 3e, 3g, 3h, 4a, 4b and 4h, exhibited antinociceptive potentiation comparable to benzotript and proglumide. In order to identify the essential chemical structural features important for this potentiation, molecular modeling and quantitative structure activity relationship (QSAR) studies have been carried out in the S and R enantiomers of some of these semi-rigid compounds. The 3D-biophore models, common to all molecules of the training set have been derived. These models with superimposition (match value >0.25) depicted three biophoric sites one each for, pi/hydrophobic interactions, hydrogen bonding and ionic interactions among the phenyl/pyrrole ring, indole nitrogen, amidic oxygen, pyridyl nitrogen and lone pair of amidic oxygen. The total hydrophobicity and S absolute stereochemistry are found to positively contribute to potentiation of antinociception induced by morphine and the resulting quantitative pharmacophoric model with good correlation is found to well describe the observed activity.

Molecular modeling and 3D-QSAR studies in 2-aziridinyl-and 2,3-bis(aziridinyl)-1,4-naphthoquinonyl sulfonate and acylate derivatives as potential antimalarial agents

Malaria is still continuing to be one of the most dreadful diseases of the tropical countries particularly due to the development of resistance to the existing antimalarials. From observed, antimalarial activity of 2-aziridinyl- and 2,3-bis(aziridinyl)-1,4-naphthoquinonyl sulfonate and acylate derivatives acting through redox cycling mechanism, molecular modeling and three dimensional-quantitative structure activity relationship (3D-QSAR) studies have been carried out on a set of 63 compounds to identify important pharmacophors. Among several 3D-QSAR models generated, three models with correlation coefficient r > 0.82, match > 0.60 and chance = 0.00 have shown two common biophoric sites: one being the oxygen atom at position 1 of the naphthoquinone ring in terms of pi-population, charge and electron donating ability while the second being the center of the phenyl ring in terms of its 6pi-electrons. In addition to these sites, the models also share two common secondary sites: one positively contributing H-acceptor site while the second site contributing negatively in terms of steric refractivity. All these models showed good agreement between the experimental, calculated and predicted antimalarial activities.

The synthesis of cyclonucleotides with fixed glycosidic bond linkages as putative agonists for P2-purinergic receptors

Cyclonucleotides with fixed glycosidic bond linkages were investigated as possible ligands for purinoceptors in PC12 cells. P2Y2-purinoceptors were not activated by the ATP analogue, 8,2'-thioanhydroadenosine-5'-triphosphate (4) and only weakly by the UTP analogue, 2,2' -anhydrouridine-5'-triphosphate (6). However, both analogues were agonists for P2X2-purinoceptors although the potencies were approximately 30-fold less than that of the parent nucleotides.

A knowledge-based approach in designing combinatorial or medicinal chemistry libraries for drug discovery. 1. A qualitative and quantitative characterization of known drug databases

The discovery of various protein/receptor targets from genomic research is expanding rapidly. Along with the automation of organic synthesis and biochemical screening, this is bringing a major change in the whole field of drug discovery research. In the traditional drug discovery process, the industry tests compounds in the thousands. With automated synthesis, the number of compounds to be tested could be in the millions. This two-dimensional expansion will lead to a major demand for resources, unless the chemical libraries are made wisely. The objective of this work is to provide both quantitative and qualitative characterization of known drugs which will help to generate "drug-like" libraries. In this work we analyzed the Comprehensive Medicinal Chemistry (CMC) database and seven different subsets belonging to different classes of drug molecules. These include some central nervous system active drugs and cardiovascular, cancer, inflammation, and infection disease states. A quantitative characterization based on computed physicochemical property profiles such as log P, molar refractivity, molecular weight, and number of atoms as well as a qualitative characterization based on the occurrence of functional groups and important substructures are developed here. For the CMC database, the qualifying range (covering more than 80% of the compounds) of the calculated log P is between -0.4 and 5.6, with an average value of 2.52. For molecular weight, the qualifying range is between 160 and 480, with an average value of 357. For molar refractivity, the qualifying range is between 40 and 130, with an average value of 97. For the total number of atoms, the qualifying range is between 20 and 70, with an average value of 48. Benzene is by far the most abundant substructure in this drug database, slightly more abundant than all the heterocyclic rings combined. Nonaromatic heterocyclic rings are twice as abundant as the aromatic heterocycles. Tertiary aliphatic amines, alcoholic OH and carboxamides are the most abundant functional groups in the drug database. The effective range of physicochemical properties presented here can be used in the design of drug-like combinatorial libraries as well as in developing a more efficient corporate medicinal chemistry library.