Design, synthesis, and in silico studies of tetrahydropyrimidine analogs as urease enzyme inhibitors

The urease enzyme, a metalloenzyme having Ni²⁺ ions, is recognized in some bacteria, fungi, and plants. Particularly, it is vital to the progress of infections induced by pathogenic microbes, such as Proteus mirabilis and Helicobacter pylori. Herein, we reported the synthesis of a series of tetrahydropyrimidine derivatives and evaluated their antiurease activity. Finally, quantitative and qualitative analyses of the derivatives were performed via in silico studies. Urease inhibitory activity was determined as the reaction of H. pylori urease with different concentrations of compounds, and thiourea was used as a standard compound. Docking and dynamics methodologies were applied to study the interactions of the best compounds with the amino acids in the active site. All compounds showed good to excellent antiurease activity. The potent compounds were not cytotoxic against the HUVEC normal cell line. Based on the docking study, compound 4e with the highest urease inhibitory activity (IC₅₀  = 6.81 ± 1.42 µM) showed chelates with both Ni²⁺ ions of the urease active site. Further, compound 4f displayed a very good inhibitory activity (IC₅₀  = 8.45 ± 1.64 μM) in comparison to thiourea (IC₅₀  = 22.03 ± 1.24 μM). The molecular docking and dynamics simulation results were correlated with the in vitro assay results. Moreover, the derivatives 4a-n followed Lipinski's rule-of-five and had drug-likeness properties.

4-Aminoquinoline-Based Adamantanes as Potential Anticholinesterase Agents in Symptomatic Treatment of Alzheimer's Disease

Considering that acetylcholinesterase (AChE) inhibition is the most important mode of action expected of a potential drug used for the treatment of symptoms of Alzheimer’s disease (AD), our previous pilot study of 4-aminoquinolines as potential human cholinesterase inhibitors was extended to twenty-two new structurally distinct 4-aminoquinolines bearing an adamantane moiety. Inhibition studies revealed that all of the compounds were very potent inhibitors of AChE and butyrylcholinesterase (BChE), with inhibition constants (K_i) ranging between 0.075 and 25 µM. The tested compounds exhibited a modest selectivity between the two cholinesterases; the most selective for BChE was compound 14, which displayed a 10 times higher preference, while compound 19 was a 5.8 times more potent inhibitor of AChE. Most of the compounds were estimated to be able to cross the blood–brain barrier (BBB) by passive transport. Evaluation of druglikeness singled out fourteen compounds with possible oral route of administration. The tested compounds displayed modest but generally higher antioxidant activity than the structurally similar AD drug tacrine. Compound 19 showed the highest reducing power, comparable to those of standard antioxidants. Considering their simple structure, high inhibition of AChE and BChE, and ability to cross the BBB, 4-aminoquinoline-based adamantanes show promise as structural scaffolds for further design of novel central nervous system drugs. Among them, two compounds stand out: compound 5 as the most potent inhibitor of both cholinesterases with a K_i constant in low nano molar range and the potential to cross the BBB, and compound 8, which met all our requirements, including high cholinesterase inhibition, good oral bioavailability, and antioxidative effect. The QSAR model revealed that AChE and BChE inhibition was mainly influenced by the ring and topological descriptors MCD, Nnum, RP, and RSIpw3, which defined the shape, conformational flexibility, and surface properties of the molecules.

In Silico Molecular Docking Analysis of Karanjin against Alzheimer's and Parkinson's Diseases as a Potential Natural Lead Molecule for New Drug Design, Development and Therapy

Parkinson’s disease (PD) and Alzheimer’s disease (AD) are neurodegenerative disorders that have emerged as among the serious health problems of the 21st century. The medications currently available to treat AD and PD have limited efficacy and are associated with side effects. Natural products are one of the most vital and conservative sources of medicines for treating neurological problems. Karanjin is a furanoflavonoid, isolated mainly from Pongamia pinnata with several medicinal plants, and has been reported for numerous health benefits. However, the effect of karanjin on AD and PD has not yet been systematically investigated. To evaluate the neuroprotective effect of karanjin, extensive in silico studies starting with molecular docking against five putative targets for AD and four targets for PD were conducted. The findings were compared with three standard drugs using Auto Dock 4.1 and Molegro Virtual Docker software. Additionally, the physiochemical properties (Lipinski rule of five), drug-likeness and parameters including absorption, distribution, metabolism, elimination and toxicity (ADMET) profiles of karanjin were also studied. The molecular dynamics (MD) simulations were performed with two selective karanjin docking complexes to analyze the dynamic behaviors and binding free energy at 100 ns time scale. In addition, frontier molecular orbitals (FMOs) and density-functional theory (DFT) were also investigated from computational quantum mechanism perspectives using the Avogadro-ORCA 1.2.0 platform. Karanjin complies with all five of Lipinski’s drug-likeness rules with suitable ADMET profiles for therapeutic use. The docking scores (kcal/mol) showed comparatively higher potency against AD and PD associated targets than currently used standard drugs. Overall, the potential binding affinity from molecular docking, static thermodynamics feature from MD-simulation and other multiparametric drug-ability profiles suggest that karanjin could be considered as a suitable therapeutic lead for AD and PD treatment. Furthermore, the present results were strongly correlated with the earlier study on karanjin in an Alzheimer’s animal model. However, necessary in vivo studies, clinical trials, bioavailability, permeability and safe dose administration, etc. must be required to use karanjin as a potential drug against AD and PD treatment, where the in silico results are more helpful to accelerate the drug development.

Drug-like Properties and Fraction Lipophilicity Index as a combined metric

Fraction Lipophicity Index (FLI) has been developed as a composite drug-like metric combining log P and log D in a weighted manner. In the present study, an extended data set confirmed the previously established drug-like FLI range 0-8 using two calculation systems for log P/log D assessment, the freeware MedChem Designer and ClogP. The dataset was split into two classes according to the percentage of fraction absorbed (%FA) - class 1 including drugs with high to medium absorption levels and class 2 including poorly absorbed drugs. The FLI and FLI-C (ClogP based FLI) drug-like range covers 92 % and 91 % of class 1 drugs, respectively. Using MlogP, a narrower drug-like FLI-M range 0-7 was established, covering 91 % of class 1 drugs. The dependence of the degree of ionization to intrinsic lipophilicity within the FLI (FLI-C, FLI-M) drug-like range as well as the inter-relation between the other Ro5 properties (Mw, HD, HA) was explored to define drug-like / non-drug-like combinations as a safer alternative to single properties for drug candidates' prioritization. In this sense, we propose a combined metric of Mw and the number of polar atoms (Mw/NO) to account for both size and polarity. Setting the value 50 as cutoff, a distinct differentiation between class 1 and class 2 drugs was obtained with Mw/NO>50 for more than 70 % of class 1 drugs, while the opposite was observed for class 2 drugs.

Tilianin: A Potential Natural Lead Molecule for New Drug Design and Development for the Treatment of Cardiovascular Disorders

Cardiovascular disorders (CVDs) are the leading risk factor for death worldwide, and research into the processes and treatment regimens has received a lot of attention. Tilianin is a flavonoid glycoside that can be found in a wide range of medicinal plants and is most commonly obtained from Dracocephalum moldavica. Due to its extensive range of biological actions, it has become a well-known molecule in recent years. In particular, numerous studies have shown that tilianin has cardioprotective properties against CVDs. Hence, this review summarises tilianin’s preclinical research in CVDs, as well as its mechanism of action and opportunities in future drug development. The physicochemical and drug-likeness properties, as well as the toxicity profile, were also highlighted. Tilianin can be a natural lead molecule in the therapy of CVDs such as coronary heart disease, angina pectoris, hypertension, and myocardial ischemia, according to scientific evidence. Free radical scavenging, inflammation control, mitochondrial function regulation, and related signalling pathways are all thought to play a role in tilianin’s cardioprotective actions. Finally, we discuss tilianin-derived compounds, as well as the limitations and opportunities of using tilianin as a lead molecule in drug development for CVDs. Overall, the scientific evidence presented in this review supports that tilianin and its derivatives could be used as a lead molecule in CVD drug development initiatives.

Strategies for designing proteolysis targeting chimaeras (PROTACs)

Proteolysis targeting chimaeras (PROTACs) is a cutting edge and rapidly growing technique for new drug discovery and development. Currently, the largest challenge in the molecular design and drug development of PROTACs is efficient identification of potent and drug-like degraders. This review aims to comprehensively summarize and analyse state-of-the-art methods and strategies in the design of PROTACs. We provide a detailed illustration of the general principles and tactics for designing potent PROTACs, highlight representative case studies, and discuss the advantages and limitations of these strategies. Particularly, structure-based rational PROTAC design and emerging new types of PROTACs (e.g., homo-PROTACs, multitargeting PROTACs, photo-control PROTACs and PROTAC-based conjugates) will be focused on.

Not Drug-like, but Like Drugs: Cnidaria Natural Products

Phylum Cnidaria has been an excellent source of natural products, with thousands of metabolites identified. Many of these have not been screened in bioassays. The aim of this study was to explore the potential of 5600 Cnidaria natural products (after excluding those known to derive from microbial symbionts), using a systematic approach based on chemical space, drug-likeness, predicted toxicity, and virtual screens. Previous drug-likeness measures: the rule-of-five, quantitative estimate of drug-likeness (QED), and relative drug likelihoods (RDL) are based on a relatively small number of molecular properties. We augmented this approach using reference drug and toxin data sets defined for 51 predicted molecular properties. Cnidaria natural products overlap with drugs and toxins in this chemical space, although a multivariate test suggests that there are some differences between the groups. In terms of the established drug-likeness measures, Cnidaria natural products have generally lower QED and RDL scores than drugs, with a higher prevalence of metabolites that exceed at least one rule-of-five threshold. An index of drug-likeness that includes predicted toxicity (ADMET-score), however, found that Cnidaria natural products were more favourable than drugs. A measure of the distance of individual Cnidaria natural products to the centre of the drug distribution in multivariate chemical space was related to RDL, ADMET-score, and the number of rule-of-five exceptions. This multivariate similarity measure was negatively correlated with the QED score for the same metabolite, suggesting that the different approaches capture different aspects of the drug-likeness of individual metabolites. The contrasting of different drug similarity measures can help summarise the range of drug potential in the Cnidaria natural product data set. The most favourable metabolites were around 210-265 Da, quite often sesquiterpenes, with a moderate degree of complexity. Virtual screening against cancer-relevant targets found wide evidence of affinities, with Glide scores <-7 in 19% of the Cnidaria natural products.

Mollusc-Derived Brominated Indoles for the Selective Inhibition of Cyclooxygenase: A Computational Expedition

Inflammation plays an important role in different chronic diseases. Brominated indoles derived from the Australian marine mollusk Dicathais orbita (D. orbita) are of interest for their anti-inflammatory properties. This study evaluates the binding mechanism and potentiality of several brominated indoles (tyrindoxyl sulfate, tyrindoleninone, 6-bromoisatin, and 6,6′-dibromoindirubin) against inflammatory mediators cyclooxygenases-1/2 (COX-1/2) using molecular docking, followed by molecular dynamics simulation, along with physicochemical, drug-likeness, pharmacokinetic (pk), and toxicokinetic (tk) properties. Molecular docking identified that these indole compounds are anchored, with the main amino acid residues, positioned in the binding pocket of the COX-1/2, required for selective inhibition. Moreover, the molecular dynamics simulation based on root mean square deviation (RMSD), radius of gyration (Rg), solvent accessible surface area (SASA), and root mean square fluctuation (RMSF) analyses showed that these natural brominated molecules transit rapidly to a progressive constant configuration during binding with COX-1/2 and seem to accomplish a consistent dynamic behavior by maintaining conformational stability and compactness. The results were comparable to the Food and Drug Administration (FDA)-approved selective COX inhibitor, aspirin. Furthermore, the free energy of binding for the compounds assessed by molecular mechanics–Poisson–Boltzmann surface area (MM–PBSA) confirmed the binding capacity of indoles towards COX-1/2, with suitable binding energy values except for the polar precursor tyrindoxyl sulfate (with COX-1). The physicochemical and drug-likeness analysis showed zero violations of Lipinski’s rule, and the compounds are predicted to have excellent pharmacokinetic profiles. These indoles are projected to be non-mutagenic and free from hepatotoxicity, with no inhibition of human ether-a-go–go gene (hERG) I inhibitors, and the oral acute toxicity LD₅₀ in rats is predicted to be similar or lower than aspirin. Overall, this work has identified a plausible mechanism for selective COX inhibition by natural marine indoles as potential therapeutic candidates for the mitigation of inflammation.

Multi-objective Genetic Algorithm for De Novo Drug Design (MoGADdrug)

BACKGROUND

A multi-objective genetic algorithm for De novo drug design (MoGADdrug) has been proposed in this paper for the design of novel drug-like molecules similar to some reference molecules. The algorithm developed accepts a set of fragments extracted from approved drugs and available in fragment libraries and combines them according to specified rules to discover new drugs through the in-silico method.

METHODS

For this process, a genetic algorithm has been used, which encodes the fragments as genes of variable length chromosomes and applies various genetic operators throughout the generations. A weighted sum approach is used to simultaneously optimize the structural similarity of the new drug to a reference molecule as well as its drug-likeness property.

RESULTS

Five reference molecules namely Lidocaine, Furano-pyrimidine derivative, Imatinib, Atorvastatin and Glipizide have been chosen for the performance evaluation of the algorithm.

CONCLUSION

Also, the newly designed molecules were analyzed using ZINC, PubChem databases and docking investigations.

Cheminformatic Characterization of Natural Antimicrobial Products for the Development of New Lead Compounds

The growing antimicrobial resistance (AMR) of pathogenic organisms to currently prescribed drugs has resulted in the failure to treat various infections caused by these superbugs. Therefore, to keep pace with the increasing drug resistance, there is a pressing need for novel antimicrobial agents, especially from non-conventional sources. Several natural products (NPs) have been shown to display promising in vitro activities against multidrug-resistant pathogens. Still, only a few of these compounds have been studied as prospective drug candidates. This may be due to the expensive and time-consuming process of conducting important studies on these compounds. The present review focuses on applying cheminformatics strategies to characterize, prioritize, and optimize NPs to develop new lead compounds against antimicrobial resistance pathogens. Moreover, case studies where these strategies have been used to identify potential drug candidates, including a few selected open-access tools commonly used for these studies, are briefly outlined.

Chalcones as Promising Antitumor Agents by Targeting the p53 Pathway: An Overview and New Insights in Drug-Likeness

The p53 protein is one of the most important tumor suppressors that are frequently inactivated in cancer cells. This inactivation occurs either because the TP53 gene is mutated or deleted, or due to the p53 protein inhibition by endogenous negative regulators, particularly murine double minute (MDM)2. Therefore, the reestablishment of p53 activity has received great attention concerning the discovery of new cancer therapeutics. Chalcones are naturally occurring compounds widely described as potential antitumor agents through several mechanisms, including those involving the p53 pathway. The inhibitory effect of these compounds in the interaction between p53 and MDM2 has also been recognized, with this effect associated with binding to a subsite of the p53 binding cleft of MDM2. In this work, a literature review of natural and synthetic chalcones and their analogues potentially interfering with p53 pathway is presented. Moreover, in silico studies of drug-likeness of chalcones recognized as p53-MDM2 interaction inhibitors were accomplished considering molecular descriptors, biophysiochemical properties, and pharmacokinetic parameters in comparison with those from p53-MDM2 in clinical trials. With this review, we expect to guide the design of new and more effective chalcones targeting the p53 pathway.

Cheminformatic Profiling and Hit Prioritization of Natural Products with Activities against Methicillin-Resistant Staphylococcus aureus (MRSA)

Several natural products (NPs) have displayed varying in vitro activities against methicillin-resistant Staphylococcus aureus (MRSA). However, few of these compounds have not been developed into potential antimicrobial drug candidates. This may be due to the high cost and tedious and time-consuming process of conducting the necessary preclinical tests on these compounds. In this study, cheminformatic profiling was performed on 111 anti-MRSA NPs (AMNPs), using a few orally administered conventional drugs for MRSA (CDs) as reference, to identify compounds with prospects to become drug candidates. This was followed by prioritizing these hits and identifying the liabilities among the AMNPs for possible optimization. Cheminformatic profiling revealed that most of the AMNPs were within the required drug-like region of the investigated properties. For example, more than 76% of the AMNPs showed compliance with the Lipinski, Veber, and Egan predictive rules for oral absorption and permeability. About 34% of the AMNPs showed the prospect to penetrate the blood–brain barrier (BBB), an advantage over the CDs, which are generally non-permeant of BBB. The analysis of toxicity revealed that 59% of the AMNPs might have negligible or no toxicity risks. Structure–activity relationship (SAR) analysis revealed chemical groups that may be determinants of the reported bioactivity of the compounds. A hit prioritization strategy using a novel “desirability scoring function” was able to identify AMNPs with the desired drug-likeness. Hit optimization strategies implemented on AMNPs with poor desirability scores led to the design of two compounds with improved desirability scores.

Novel 6-hydroxyquinolinone derivatives: Design, synthesis, antimicrobial evaluation, in silico study and toxicity profiling

Infectious diseases of bacteria and fungi have become a major risk to public health because of antibiotic and antifungal resistance. However, the availability of effective antibacterial and antifungal agents is becoming increasingly limited with growing resistance to existing drugs. In response to that, novel agents are critically needed to overcome such resistance. A new series of 6-hydroxyquinolinone 3, 4, 5a, 5b, 6a and 6b bearing different side chains were synthesized and evaluated as antimicrobials against numbers of bacteria and fungi, using inhibition zone technique. As one of these derivatives, compound 3 was identified as a potent antibacterial and antifungal agent against all tested microorganisms with good minimum inhibitory concentration values comparable to reference drugs. Molecular docking studies were performed on antibacterial and antifungal targets; microbial DNA gyrase B of Staphylococcus aureus (PDB ID: 4URO); N-myristoyltransferase of Candida albicans (PDB ID: 1IYK), respectively, to predict the most probable type of interaction at the active site of the target protein in addition to binding affinities and orientations of docked ligands. Additionally, in silico prediction in terms of detailed physicochemical ADME and toxicity profile relating drug-likeness as well as medicinal chemistry friendliness was performed to all synthesized compounds. The results indicated that a novel 4,6-dihydroxyquinolin-2(1H)-one (3) is likely to be a newly synthesized drug candidate, indicating low toxicity in addition to good in silico absorption. In order to pave the way for more logical production of such compounds, structure-activity and toxicity relationships are also discussed.

Network Pharmacological Analysis through a Bioinformatics Approach of Novel NSC765600 and NSC765691 Compounds as Potential Inhibitors of CCND1/CDK4/PLK1/CD44 in Cancer Types

Simple Summary

Around 14 million new cancer cases, rate are reported annually, with high mortality worldswide, several mechanisms are associated with complexities in cancer, which leads to resistance to current therapeutic interventions in cancer patients. The aim of this study was to identify molecular genes responsible for cancer development, progression and resistances to therapeutic intervention, and also evaluate the potency of our novel compounds NSC7565600 and NSC765691 as potential target for these oncogenes. Using bioinformatics, we successfully identified CCND1/CDK4/PLK1/CD44 as oncogenic signatures, which drives cancer progression and resistance to treatment, and as potential druggable candidates for both NSC7565600 and NSC765691 small molecules. We also showed the antiproliferative and cytotoxic effects of these compounds against a panel of NCI-60 cancer cell lines. This suggests the potential of NSC765600 and NSC765691 compounds to inhibit CCND1/CDK4/PLK1/CD44 expressions in cancer.

Abstract

Cyclin D1 (CCND1) and cyclin-dependent kinase 4 (CDK4) both play significant roles in regulating cell cycle progression, while polo-like kinase 1 (PLK1) regulates cell differentiation and tumor progression, and activates cancer stem cells (CSCs), with the cluster of differentiation 44 (CD44) surface marker mostly being expressed. These oncogenes have emerged as promoters of metastasis in a variety of cancer types. In this study, we employed comprehensive computational and bioinformatics analyses to predict drug targets of our novel small molecules, NSC765600 and NSC765691, respectively derived from diflunisal and fostamatinib. The target prediction tools identified CCND1/CDK4/PLK1/CD44 as target genes for NSC765600 and NSC765691 compounds. Additionally, the results of our in silico molecular docking analysis showed unique ligand–protein interactions with putative binding affinities of NSC765600 and NSC765691 with CCND1/CDK4/PLK1/CD44 oncogenic signaling pathways. Moreover, we used drug-likeness precepts as our guidelines for drug design and development, and found that both compounds passed the drug-likeness criteria of molecular weight, polarity, solubility, saturation, flexibility, and lipophilicity, and also exhibited acceptable pharmacokinetic properties. Furthermore, we used development therapeutics program (DTP) algorithms and identified similar fingerprints and mechanisms of NSC765600 and NSC765691 with synthetic compounds and standard anticancer agents in the NCI database. We found that NSC765600 and NSC765691 displayed antiproliferative and cytotoxic effects against a panel of NCI-60 cancer cell lines. Based on these finding, NSC765600 and NSC765691 exhibited satisfactory levels of safety with regard to toxicity, and met all of the required criteria for drug-likeness precepts. Currently, further in vitro and in vivo investigations in tumor-bearing mice are in progress to study the potential treatment efficacies of the novel NSC765600 and NSC765691 small molecules.

The molecular interaction of human anti-apoptotic proteins and in silico ADMET, drug-likeness and toxicity computation of N-cyclohexylmethacrylamide

Cancer is an uncontrolled growth of normal cells and apoptosis has an important role in cancer progression and cancer treatment. Antiapoptotic proteins are overexpressed in several tumors including breast, brain, lung cancer cells. The protein-ligand interaction has a critical role in drug designing. The present study aims to evaluate the interaction of synthesized N-cyclohexylmethacrylamide (NCMA) with proteins using in silico molecular docking and toxicity analyses. The NCMA monomer was synthesized and characterized by our team, previously. Kinetics stability, binding affinities and toxic potential of protein-NCMA complex were examined with the aid of molecular simulation. The toxicity results of this study indicate that NCMA is a sample with low toxic potential. According to the docking results, NCMA may be a drug active substance with chemical modifications and toxicity results support this situation. The drug-likeness and ADMET parameters were screened properties of NCMA.

Synthesis, molecular docking and ADME studies of thiazole-thiazolidinedione hybrids as antimicrobial agents

New thiazole-thiazolidinedione hybrids (5a-k) were efficiently synthesized and evaluated for their in-vitro antimicrobial activity against four fungal and bacterial strains. The chemical structures of the compounds were elucidated by FTIR, ¹H NMR, and ¹³C NMR spectral data. Most of the synthesized compounds were sensitive against gram positive, gram negative bacterial and fungal strains. Among the synthesized molecules, compounds 5h, and 5i exhibited promising inhibitory activity against all selected fungal strains and gram positive bacteria namely, Staphylococcus aureus, and Enterococcus faecalis. The molecular docking results predicted that the thiazole-thiazolidinedione derivatives bind to the active site protein ATP-binding pocket from E. coli, S. aureus and C. albicans with good interaction energy scores. Ct-DNA was used to evaluate the binding interactions of the selected compounds by means of absorption spectroscopy. To further characterize the drug-likeness and ADME properties were calculated using the Qikprop, the result of present study suggests that thiazole-thiazolidinedione hybrid could be an interesting approach for the design of new antimicrobial agents.Communicated by Ramaswamy H. Sarma.

Application of QSAR Method in the Design of Enhanced Antimalarial Derivatives of Azetidine-2-carbonitriles, their Molecular Docking, Drug-likeness, and SwissADME Properties

The resistance of the P. falciparum strain to some of the antimalarial drugs has been a dominant dilemma facing the treatment of this fetid disease. This necessitates the detection and development of new antimalarial agents targeting the P. falciparum. Azetidine-2-carbonitriles reported for its antimalarial activities, could provide an alternative to the customized antimalarial drugs. Leading to the use of quantitative structure-activity relationship (QSAR) studies, which relates the structures of Azetidine-2-carbonitriles with their activities to generate predictive models. The structures were optimized using density functional theory (DFT) DFT/B3LYP/6-31G* basis set to generate their molecular descriptors, where five predictive models were constructed using the generated descriptors. The models were constructed using the genetic function algorithm component of a material studio, where the model with good statistical parameters, high coefficient of determination (R2) = 0.9465, cross-validated R2 (Q2cv) = 0.8981, Q2 (L4O)cv = 0.9272, and highest external validated R2 (R2 pred) = 0.6915 was selected as the best model. These statistical results show the robustness, excellent power of prediction, and validity of the selected model. The descriptor, SpMax2_Bhp (the maximum absolute eigenvalue of Barysz matrix for n = 2 was weighted by polarizability), was revealed to be the most influential in the model due to its highest mean effect. The descriptor played a role in the design of sixteen (16) theoretical derivatives of Azetidine-2-carbonitriles using compound 25 as the design template by increasing polarizability of the compounds through substitution of the various group with electron deactivating groups (F, I, Cl, SO3H, CN, NO2, etc.) at different position of the template. The designed compounds were docked with Plasmodium falciparum dihydroorotate dehydrogenase (Pf-DHODH), giving compound D9 the highest binding energy. The designed compounds were further screened for their drug-likeness, where they all pass Lipinski's RO5. All the compounds show good skin permeability coefficient and have low Gastrointestinal absorption while few compounds D1, D2, D3, D14, and D15 inhibiting the CYP1A2.

Multi-objective optimization methods in novel drug design

Introduction: In multi-objective drug design, optimization gains importance, being upgraded to a discipline that attracts its own research. Current strategies are broadly classified into single - objective optimization (SOO) and multi-objective optimization (MOO).Areas covered: Starting with SOO and the ways used to incorporate multiple criteria into it, the present review focuses on MOO techniques, their comparison, advantages, and restrictions. Pareto analysis and the concept of dominance stand in the core of MOO. The Pareto front, Pareto ranking, and limitations of Pareto-based methods, due to high dimensions and data uncertainty, are outlined. Desirability functions and the weighted sum approaches are described as stand-alone techniques to transform the MOO problem to SOO or in combination with pareto analysis and evolutionary algorithms. Representative applications in different drug research areas are also discussed.Expert opinion: Despite their limitations, the use of combined MOO techniques, as well as being complementary to SOO or in conjunction with artificial intelligence, contributes dramatically to efficient drug design, assisting decisions and increasing success probabilities. For multi-target drug design, optimization is supported by network approaches, while applicability of MOO to other fields like drug technology or biological complexity opens new perspectives in the interrelated fields of medicinal chemistry and molecular biology.

In silico drug discovery of IKK-β inhibitors from 2-amino-3-cyano-4-alkyl-6-(2-hydroxyphenyl) pyridine derivatives based on QSAR, docking, molecular dynamics and drug-likeness evaluation studies

The Inhibitor of IKK-β (nuclear factor kappa B kinase subunit beta), a specific modulator of NF-κB (nuclear factor-κB), is considered a valid target to discover new active compounds for various cancers and rheumatoid arthritis treatment. In this study a series of thirty 2-amino-3-cyano-4-alkyl-6-(2-hydroxyphenyl) pyridine derivatives was involved for a quantitative structure activity relationship model (QSAR) elaboration which allows the prediction of the pIC50 values of new designed compounds. The model can be used to predict the activity of new compounds within its applicability domain. Then a molecular docking study was carried out to identify the interactions between the compounds and the amino acids of the active site. After that, golden triangle, Veber's rule, and Lipinski's rule properties were calculated to identify the drug-likeness properties of the investigated compounds. Finally, in-silico-toxicity studies were performed to predict the toxicity of the new designed compounds. The analysis of the results of QSAR model and molecular docking succeeded to screen 21 interesting compounds with better inhibitory concentration having a good affinity to IKK-β. All compounds were within the range set by Veber's rule and Lipinski's rule. the analysis of golden triangle showed that the thirty 2-amino-3-cyano-4-alkyl-6-(2-hydroxyphenyl) pyridine derivatives would not have clearance and cell membrane permeability problems except comp6 comp12,comp20, comp21, and comp26.As for the new designed compounds, their properties may have these problems, except two compounds which are: A8m, A8p. The A1m, A1p, A3p and A11m compounds were predicted to be nontoxic. These findings indicate that the novel potent candidate drugs have promising potential to IKK-β enzyme inhibition and should motivate future experimental investigations.Communicated by Ramaswamy H. Sarma.

Scopy: an integrated negative design python library for desirable HTS/VS database design

BACKGROUND

High-throughput screening (HTS) and virtual screening (VS) have been widely used to identify potential hits from large chemical libraries. However, the frequent occurrence of 'noisy compounds' in the screened libraries, such as compounds with poor drug-likeness, poor selectivity or potential toxicity, has greatly weakened the enrichment capability of HTS and VS campaigns. Therefore, the development of comprehensive and credible tools to detect noisy compounds from chemical libraries is urgently needed in early stages of drug discovery.

RESULTS

In this study, we developed a freely available integrated python library for negative design, called Scopy, which supports the functions of data preparation, calculation of descriptors, scaffolds and screening filters, and data visualization. The current version of Scopy can calculate 39 basic molecular properties, 3 comprehensive molecular evaluation scores, 2 types of molecular scaffolds, 6 types of substructure descriptors and 2 types of fingerprints. A number of important screening rules are also provided by Scopy, including 15 drug-likeness rules (13 drug-likeness rules and 2 building block rules), 8 frequent hitter rules (four assay interference substructure filters and four promiscuous compound substructure filters), and 11 toxicophore filters (five human-related toxicity substructure filters, three environment-related toxicity substructure filters and three comprehensive toxicity substructure filters). Moreover, this library supports four different visualization functions to help users to gain a better understanding of the screened data, including basic feature radar chart, feature-feature-related scatter diagram, functional group marker gram and cloud gram.

CONCLUSION

Scopy provides a comprehensive Python package to filter out compounds with undesirable properties or substructures, which will benefit the design of high-quality chemical libraries for drug design and discovery. It is freely available at https://github.com/kotori-y/Scopy.

Targeting COVID-19 (SARS-CoV-2) main protease through active phytochemicals of ayurvedic medicinal plants - Withania somnifera (Ashwagandha), Tinospora cordifolia (Giloy) and Ocimum sanctum (Tulsi) - a molecular docking study

COVID-19 (Coronavirus disease 2019) is a transmissible disease initiated and propagated through a new virus strain SARS-CoV-2 (Severe Acute Respiratory Syndrome Coronavirus-2) since 31^st December 2019 in Wuhan city of China and the infection has outspread globally influencing millions of people. Here, an attempt was made to recognize natural phytochemicals from medicinal plants, in order to reutilize them against COVID-19 by the virtue of molecular docking and molecular dynamics (MD) simulation study. Molecular docking study showed six probable inhibitors against SARS-CoV-2 M^pro (Main protease), two from Withania somnifera (Ashwagandha) (Withanoside V [10.32 kcal/mol] and Somniferine [9.62 kcal/mol]), one from Tinospora cordifolia (Giloy) (Tinocordiside [8.10 kcal/mol]) and three from Ocimum sanctum (Tulsi) (Vicenin [8.97 kcal/mol], Isorientin 4'-O-glucoside 2″-O-p-hydroxybenzoagte [8.55 kcal/mol] and Ursolic acid [8.52 kcal/mol]). ADMET profile prediction showed that the best docked phytochemicals from present work were safe and possesses drug-like properties. Further MD simulation study was performed to assess the constancy of docked complexes and found stable. Hence from present study it could be suggested that active phytochemicals from medicinal plants could potentially inhibit M^pro of SARS-CoV-2 and further equip the management strategy against COVID-19-a global contagion. HighlightsHolistic approach of Ayurvedic medicinal plants to avenge against COVID-19 pandemic.Active phytoconstituents of Ayurvedic medicinal plants Withania somnifera (Ashwagandha), Tinospora cordifolia (Giloy) and Ocimum sanctum (Tulsi) predicted to significantly hinder main protease (M^pro or 3Cl^pro) of SARS-CoV-2.Through molecular docking and molecular dynamic simulation study, Withanoside V, Somniferine, Tinocordiside, Vicenin, Ursolic acid and Isorientin 4'-O-glucoside 2″-O-p-hydroxybenzoagte were anticipated to impede the activity of SARS-CoV-2 M^pro.Drug-likeness and ADMET profile prediction of best docked compounds from present study were predicted to be safe, drug-like compounds with no toxicity.Communicated by Ramaswamy H. Sarma.

Identification of the natural compound inhibitors against Plasmodium falciparum plasmepsin-II via common feature based screening and molecular dynamics simulations

Malaria is counted amongst the deadly disease caused by Plasmodium falciparum. Recently, plasmepsin-II enzyme has gained much importance as an attractive drug target for the exploration of antimalarials. Therefore, the common feature pharmacophore models were generated from the crystallized complexes of the plasmepsin-II proteome. These models were subjected to a series of validation procedures, i.e. test set and Güner Henry studies to enlist the representative models. The selected representative hypotheses incorporating the most essential chemical features (common ZHHA) were screened against the natural product database to retrieve the potential candidates. To ensure the selection of the drug-like candidates, prior to screening, filtering steps (Drug-likeness and ADMET filters) were employed on the selected database. To study the interaction pattern of the candidates within the protein, these molecules were advanced to the molecular docking studies. Subsequently, based on the selected cut-off criteria obtained via redocking of the reference (4Z22), 15 compounds showed higher docking score (> -16.05 kcal/mol), and displayed the presence of hydrogen bonding with the crucial amino acids, i.e. Asp34 and Asp214. Further, the stability of the docked molecules was scrutinized via molecular dynamics simulations, and the results were compared with the reference compound 4Z22. All the docked compounds showed stable dynamics behaviour. Thus, in the present contribution, the combination of screening and stability procedures resulted in the identification of 15 hits that can serve as a new chemical space in the designing of the novel antimalarials.Communicated by Ramaswamy H. Sarma.

Cyanobacterial metabolites as promising drug leads against the Mpro and PLpro of SARS-CoV-2: an in silico analysis

A novel severe acute respiratory syndrome coronavirus (SARS-CoV-2) has emerged as the causative agent behind the coronavirus disease 2019 (COVID-19) pandemic. Treatment efforts have been severely impeded due to the lack of specific effective antiviral drugs for the treatment of COVID-associated pathologies. In the present research endeavour the inhibitory prospects of cyanobacterial metabolites were assessed at the active binding pockets of the two vital SARS-CoV-2 proteases namely, main protease (M^pro) and the papain-like protease (PL^pro) that proteolytically process viral polyproteins and facilitate viral replication, employing an in silico molecular interaction-based approach. It was evident from our analysis based on the binding energy scores that the metabolites cylindrospermopsin, deoxycylindrospermopsin, carrageenan, cryptophycin 52, eucapsitrione, tjipanazole, tolyporphin and apratoxin A exhibited promising inhibitory potential against the SARS-CoV-2 M^pro. The compounds cryptophycin 1, cryptophycin 52 and deoxycylindrospermopsin were observed to display encouraging binding energy scores with the PL^pro of SARS-CoV-2. Subsequent estimation of physicochemical properties and potential toxicity of the metabolites followed by robust molecular dynamics simulations and analysis of MM-PBSA energy scoring function established deoxycylindrospermopsin as the most promising inhibitory candidate against both SARS-CoV-2 proteases. Present research findings bestow ample scopes to further exploit the potential of deoxycylindrospermopsin as a successful inhibitor of SARS-CoV-2 in vitro and in vivo and pave the foundation for the development of novel effective therapeutics against COVID-19.

Communicated by Ramaswamy H. Sarma

Natural-like products as potential SARS-CoV-2 Mpro inhibitors: in-silico drug discovery

In December 2019, a COVID-19 epidemic was discovered in Wuhan, China, and since has disseminated around the world impacting human health for millions. Herein, in-silico drug discovery approaches have been utilized to identify potential natural products (NPs) as Severe Acute Respiratory Syndrome coronavirus 2 (SARS-CoV-2) main protease (M^pro) inhibitors. The MolPort database that contains over 100,000 NPs was screened and filtered using molecular docking techniques. Based on calculated docking scores, the top 5,000 NPs/natural-like products (NLPs) were selected and subjected to molecular dynamics (MD) simulations followed by molecular mechanics-generalized Born surface area (MM-GBSA) binding energy calculations. Combined 50 ns MD simulations and MM-GBSA calculations revealed nine potent NLPs with binding affinities (ΔG_binding) > -48.0 kcal/mol. Interestingly, among the identified NLPs, four bis([1,3]dioxolo)pyran-5-carboxamide derivatives showed ΔG_binding > -56.0 kcal/mol, forming essential short hydrogen bonds with HIS163 and GLY143 amino acids via dioxolane oxygen atoms. Structural and energetic analyses over 50 ns MD simulation demonstrated NLP-M^pro complex stability. Drug-likeness predictions revealed the prospects of the identified NLPs as potential drug candidates. The findings are expected to provide a novel contribution to the field of COVID-19 drug discovery.Communicated by Ramaswamy H. Sarma.

Exploration and evaluation of bioactive phytocompounds against BRCA proteins by in silico approach

The proteins encoded by the two major breast cancer genes (BRCA1 and BRCA2), ensure the stability of DNA and prevent uncontrolled cell growth; mutation of these genes is linked to the development of hereditary breast cancers. Exploration of human breast cancer inhibitors plays a vital role in the drug discovery process. In the current work, in silico studies were performed which involves a computational approach for the identification of active phytocompounds from the diverse set of medicinal plant products against the BRCA receptor. The in silico study through pharmacokinetics and pharmacodynamics properties shown promising outcomes for these phytocompounds data set as breast cancer inhibitors. It was observed that the compounds conformed to the Lipinski's rule of five and had good bioavailability. The drug-likeness model score and ADMET profile of the designed ligands also established their potential as a drug candidate. The docking study provided useful insights on potential target-lead interactions and indicated that the newly designed leads had a good binding affinity for BRCA targets. A pharmacophore model was built to explore the scaffolds for BRCA inhibitory activity. An effort is made to screen an inhibitor against BRCA targets by combining the use of ADMET, docking score, and pharmacophore model.Communicated by Ramaswamy H. Sarma.

Natural compounds from Clerodendrum spp. as possible therapeutic candidates against SARS-CoV-2: An in silico investigation

The COVID-19 pandemic caused by the novel coronavirus SARS-CoV-2 has rattled global public health, with researchers struggling to find specific therapeutic solutions. In this context, the present study employed an in silico approach to assess the inhibitory potential of the phytochemicals obtained from GC-MS analysis of twelve Clerodendrum species against the imperative spike protein, main protease enzyme M^pro and RNA-dependent RNA polymerase (RdRp) of SARS-CoV-2. An extensive molecular docking investigation of the phytocompounds at the active binding pockets of the viral proteins revealed promising inhibitory potential of the phytochemicals taraxerol, friedelin and stigmasterol. Decent physicochemical attributes of the compounds in accordance with Lipinski’s rule of five and Veber’s rule further established them as potential therapeutic candidates against SARS-CoV-2. Molecular mechanics-generalized Born surface area (MM-GBSA) binding free energy estimation revealed that taraxerol was the most promising candidate displaying the highest binding efficacy with all the concerned SARS-CoV-2 proteins included in the present analysis. Our observations were supported by robust molecular dynamics simulations of the complexes of the viral proteins with taraxerol for a timescale of 40 nanoseconds. It was striking to note that taraxerol exhibited better binding energy scores with the concerned viral proteins than the drugs that are specifically targeted against them. The present results promise to provide new avenues to further evaluate the potential of the phytocompound taraxerol in vitro and in vivo towards its successful deployment as a SARS-CoV-2 inhibitor and combat the catastrophic COVID-19.

Communicated by Ramaswamy H. Sarma

Grape Cane Extracts as Multifunctional Rejuvenating Cosmetic Ingredient: Evaluation of Sirtuin Activity, Tyrosinase Inhibition and Bioavailability Potential

Grape canes are waste biomass of viticulture containing bioactive polyphenols valuable in cosmetics. Whereas several studies reported the cosmetic activities of E-resveratrol, only few described the potential of E-ε-viniferin, the second major constituent of grape cane extracts (GCE), and none of them investigated GCE as a natural blend of polyphenols for cosmetic applications. In this study, we considered the potential of GCE from polyphenol-rich grape varieties as multifunctional cosmetic ingredients. HPLC analysis was performed to quantify major polyphenols in GCE i.e., catechin, epicatechin, E-resveratrol, E-piceatannol, ampelopsin A, E-ε-viniferin, hopeaphenol, isohopeaphenol, E-miyabenol C and E-vitisin B from selected cultivars. Skin whitening potential through tyrosinase inhibition assay and the activation capacity of cell longevity protein (SIRT1) of GCE were compared to pure E-resveratrol and E-ε-viniferin. Drug-likeness of GCE polyphenols were calculated, allowing the prediction of skin permeability and bioavailability. Finally, the present data enabled the consideration of GCE from polyphenol-rich varieties as multifunctional cosmetic ingredients in accordance with green chemistry practices.

In Silico Screening for Novel Leucine Aminopeptidase Inhibitors with 3,4-Dihydroisoquinoline Scaffold

Cancers are the leading cause of deaths worldwide. In 2018, an estimated 18.1 million new cancer cases and 9.6 million cancer-related deaths occurred globally. Several previous studies have shown that the enzyme, leucine aminopeptidase is involved in pathological conditions such as cancer. On the basis of the knowledge that isoquinoline alkaloids have antiproliferative activity and inhibitory activity towards leucine aminopeptidase, the present study was conducted a study which involved database search, virtual screening, and design of new potential leucine aminopeptidase inhibitors with a scaffold based on 3,4-dihydroisoquinoline. These compounds were then filtered through Lipinski's "rule of five," and 25 081 of them were then subjected to molecular docking. Next, three-dimensional quantitative structure-activity relationship (3D-QSAR) study was performed for the selected group of compounds with the best binding score results. The developed model, calculated by leave-one-out method, showed acceptable predictive and descriptive capability as represented by standard statistical parameters r² (0.997) and q² (0.717). Further, 35 compounds were identified to have an excellent predictive reliability. Finally, nine selected compounds were evaluated for drug-likeness and different pharmacokinetics parameters such as absorption, distribution, metabolism, excretion, and toxicity. Our methodology suggested that compounds with 3,4-dihydroisoquinoline moiety were potentially active in inhibiting leucine aminopeptidase and could be used for further in-depth in vitro and in vivo studies.

A Supramolecular Approach to Structure-Based Design with A Focus on Synthons Hierarchy in Ornithine-Derived Ligands: Review, Synthesis, Experimental and in Silico Studies

The success of innovative drugs depends on an interdisciplinary and holistic approach to their design and development. The supramolecular architecture of living systems is controlled by non-covalent interactions to a very large extent. The latter are prone to extensive cooperation and like a virtuoso play a symphony of life. Thus, the design of effective ligands should be based on thorough knowledge on the interactions at either a molecular or high topological level. In this work, we emphasize the importance of supramolecular structure and ligand-based design keeping the potential of supramolecular H-bonding synthons in focus. In this respect, the relevance of supramolecular chemistry for advanced therapies is appreciated and undisputable. It has developed tools, such as Hirshfeld surface analysis, using a huge data on supramolecular interactions in over one million structures which are deposited in the Cambridge Structure Database (CSD). In particular, molecular interaction surfaces are useful for identification of macromolecular active sites followed by in silico docking experiments. Ornithine-derived compounds are a new, promising class of multi-targeting ligands for innovative therapeutics and cosmeceuticals. In this work, we present the synthesis together with the molecular and supramolecular structure of a novel ornithine derivative, namely N-α,N-δ)-dibenzoyl-(α)-hydroxymethylornithine, 1. It was investigated by modern experimental and in silico methods in detail. The incorporation of an aromatic system into the ornithine core induces stacking interactions, which are vital in biological processes. In particular, rare C=O…π intercontacts have been identified in 1. Supramolecular interactions were analyzed in all structures of ornithine derivatives deposited in the CSD. The influence of substituent was assessed by the Hirshfeld surface analysis. It revealed that the crystal packing is stabilized mainly by H…O, O…H, C…H, Cl (Br, F)…H and O…O interactions. Additionally, π…π, C-H…π and N-O…π interactions were also observed. All relevant H-bond energies were calculated using the Lippincott and Schroeder H-bond model. A library of synthons is provided. In addition, the large synthons (Long-Range Synthon Aufbau Module) were considered. The DFT optimization either in vacuo or in solutio yields very similar molecular species. The major difference with the relevant crystal structure was related to the conformation of terminal benzoyl C15-C20 ring. Furthermore, in silico prediction of the extensive physicochemical ADME profile (absorption, distribution, metabolism and excretion) related to the drug-likeness and medicinal chemistry friendliness revealed that a novel ornithine derivative 1 has the potential to be a new drug candidate. It has shown good in silico absorption and very low toxicity.

Identification of High-Affinity Inhibitors of Cyclin-Dependent Kinase 2 Towards Anticancer Therapy

Cyclin-dependent kinase 2 (CDK2) is an essential protein kinase involved in the cell cycle regulation. The abnormal activity of CDK2 is associated with cancer progression and metastasis. Here, we have performed structure-based virtual screening of the PubChem database to identify potent CDK2 inhibitors. First, we retrieved all compounds from the PubChem database having at least 90% structural similarity with the known CDK2 inhibitors. The selected compounds were subjected to structure-based molecular docking studies to investigate their pattern of interaction and estimate their binding affinities with CDK2. Selected compounds were further filtered out based on their physicochemical and ADMET properties. Detailed interaction analysis revealed that selected compounds interact with the functionally important residues of the active site pocket of CDK2. All-atom molecular dynamics simulation was performed to evaluate conformational changes, stability and the interaction mechanism of CDK2 in-complex with the selected compound. We found that binding of 6-N,6-N-dimethyl-9-(2-phenylethyl)purine-2,6-diamine stabilizes the structure of CDK2 and causes minimal conformational change. Finally, we suggest that the compound (PubChem ID 101874157) would be a promising scaffold to be further exploited as a potential inhibitor of CDK2 for therapeutic management of cancer after required validation.

Structure-based Discovery of Narirutin as a Shikimate kinase Inhibitor with Anti-tubercular Potency

BACKGROUND

Shikimate pathway is essential for tubercular bacillus but it is absent in mammals. Therefore, Shikimate kinase and other enzymes in the pathway are potential targets for the development of novel anti-tuberculosis drugs.

OBJECTIVE

In the present study, Shikimate kinase is selected as the target for in silico screening of phytochemicals with an aim to discover a novel herbal drug against Mycobacterium tuberculosis (Mtb).

METHODS

A structure-based drug discovery approach is undertaken for the execution of the objective. Virtual screening of phytochemical database NPACT against the target, Shikimate kinase (PDB ID 3BAF), is carried out followed by toxicity and drug-likeness filtration. Finally, a lead, narirutin was selected for in vitro anti-tubercular study.

RESULTS

Narirutin, present in citrus fruits, emerges as the lead. It is considered to be non-toxic with predicted high LD50 value, 12000 mg/kg body weight. The phytochemical is tested for its antitubercular activity in vitro. It has MIC99 62.5 μg/mL against the MtbH37Rv strain.

CONCLUSION

This is the first-ever report to show anti-tuberculosis potency of narirutin.

Herbal compounds for rheumatoid arthritis: Literatures review and cheminformatics prediction

Rheumatoid arthritis (RA) is a systemic disease characterized by autoimmunity, joint inflammation, and cartilage destruction, which affects 0.5-1% of the population. Many compounds from herbal medicines show the potentials to treat RA. On this basis, the compounds with good pharmacokinetic behaviors and drug-likeness properties will be further studied and developed. Therefore, the herbal compounds with anti-RA activities were reviewed in this paper, and the cheminformatics tools were used to predict their drug-likeness properties and pharmacokinetic parameters. A total of 90 herbal compounds were analyzed, which were reported to be effective on RA models through anti-inflammation, chondroprotection, immunoregulation, antiangiogenesis, and antioxidation. Most of the herbal compounds have good drug-likeness properties. Most of the compounds can be an alternative and valuable source for anti-RA drug discovery.

Fraction Lipophilicity Index (FLI). A drug-like metric for orally administered ionizable drugs

Fraction Lipophilicity Index (FLI) was developed as a metric for assessing drug likeness of ionizable oral drugs. Considering that both log P and log D have distinct roles in drug action, the metric FLI allocates lipophilicity to a pH dependent neutral fraction of the molecule and is a weighted combination of log P and log D. It is expressed by equation: FLI = 2 x log P-│log D│. A dataset of 368 basic and acidic drugs was analyzed. Based on available % absorption data, drugs were classified into class 1 (268 drugs) and class 2 (100 drugs). The freeware MedChem Designer was used for log P and log D calculations at pH 7.4 and pH 5.5 for acids. Based on class 1, a drug-like FLI range 0-8 was defined. FLI distribution for class 2 is shifted towards significantly lower values. Comparison of FLI with rule of 5 (Ro5) shows that it leads to fewer values outside the established range than the corresponding log P violations for class 1. For class 2 it gives more alerts than Ro5 and can be considered complementary to Ro5, while it also sets lower limits to discriminate drugs with poor absorption.

Novel phthalimide based analogues: design, synthesis, biological evaluation, and molecular docking studies

Pyrazolylphthalimide derivative 4 was synthesized and reacted with different reagents to afford the target compounds imidazopyrazoles 5-7, pyrazolopyrimidines 9, 12, 14 and pyrazolotriazines 16, 17 containing phthalimide moiety. The prepared compounds were established by different spectral data and elemental analyses. Additionally, all synthesized derivatives were screened for their antibacterial activity against four types of Gram + ve and Gram-ve strains, and for antifungal activity against two fungi micro-organisms by well diffusion method. Moreover, the antiproliferative activity was tested for all compounds against human liver (HepG-2) cell line in comparison with the reference vinblastine. Moreover, drug-likeness and toxicity risk parameters of the newly synthesized compounds were calculated using in silico studies. The data from structure-actvity relationship (SAR) analysis suggested that phthalimide derivative bearing 3-aminopyrazolone moiety, 4 illustrated the best antimicrobial and antitumor activities and might be considered as a lead for further optimization. To investigate the mechanism of the antimicrobial and anticancer activities, enzymatic assay and molecular docking studies were carried out on E. coli topoisomerase II DNA gyrase B and VEGFR-2 enzymes.

Methoxychalcones: Effect of Methoxyl Group on the Antifungal, Antibacterial and Antiproliferative Activities

BACKGROUND

Chalcones substituted by methoxyl groups have presented a broad spectrum of bioactivities, including antifungal, antibacterial and antiproliferative effects. However, a clear and unambiguous investigation about the relevance of this substituent on the chalcone framework has not been described.

OBJECTIVE

The purpose of this work is to assess the antibacterial, antifungal and antiproliferative activities of the two series of seventeen synthesized regioisomeric methoxychalcones. Series I and II were constituted by chalcones substituted by methoxyl groups on rings A (5-12) and B (13-21), respectively. In addition, the library of methoxychalcones was submitted to in silico drug-likeness and pharmacokinetics properties predictions.

METHODS

Methoxychalcones were synthesized and their structures were confirmed by NMR spectral data analyses. Evaluations of antimicrobial activity were performed against five species of Candida, two Gram-negative and five Gram-positive species. For antiproliferative activity, methoxychalcones were evaluated against four human tumorigenic cell lines, as well as human non-tumorigenic keratinocytes. Drug-likeness and pharmacokinetics properties were predicted using Molinspiration and PreADMET toolkits.

RESULTS

In general, chalcones of series I are the most potent antifungal, antibacterial and antiproliferative agents. 3', 4', 5'-Trimethoxychalcone (12) demonstrated potent antifungal activity against Candida krusei (MIC = 3.9 μg/mL), eight times more potent than fluconazole (reference antifungal drug). 3'-Methoxychalcone (6) displayed anti-Pseudomonas activity (MIC = 7.8 μg/mL). 2',5'-Dimethoxychalcone (9) displayed potent antiproliferative effect against C-33A (cervix), A-431 (skin) and MCF-7 (breast), with IC50 values ranging from 7.7 to 9.2 μM. Its potency was superior to curcumin (reference antiproliferative compound), which exhibited IC50 values ranging from 10.4 to 19.0 μM.

CONCLUSION

Our studies corroborated the relevance of methoxychalcones as antifungal, antibacterial and antiproliferative agents. In addition, we elucidated influence of the position and number of methoxyl groups toward bioactivity. In silico predictions indicated good drug-likeness and pharmacokinetics properties to the library of methoxychalcones.

Drug-1,3,4-Thiadiazole Conjugates as Novel Mixed-Type Inhibitors of Acetylcholinesterase: Synthesis, Molecular Docking, Pharmacokinetics, and ADMET Evaluation

A small library of new drug-1,3,4-thiazidazole hybrid compounds (3a⁻3i) was synthesized, characterized, and assessed for their acetyl cholinesterase enzyme (AChE) inhibitory and free radical scavenging activities. The newly synthesized derivatives showed promising activities against AChE, especially compound 3b (IC₅₀ 18.1 ± 0.9 nM), which was the most promising molecule in the series, and was substantially more active than the reference drug (neostigmine methyl sulfate; IC₅₀ 2186.5 ± 98.0 nM). Kinetic studies were performed to elucidate the mode of inhibition of the enzyme, and the compounds showed mixed-type mechanisms for inhibiting AChE. The Ki of 3b (0.0031 µM) indicates that it can be very effective, even at low concentrations. Compounds 3a⁻3i all complied with Lipinski's Rule of Five, and showed high drug-likeness scores. The pharmacokinetic parameters revealed notable lead-like properties with insignificant liver and skin-penetrating effects. The structure⁻activity relationship (SAR) analysis indicated π⁻π interactions with key amino acid residues related to Tyr124, Trp286, and Tyr341.

Prediction of Drug-Likeness Using Deep Autoencoder Neural Networks

Due to diverse reasons, most drug candidates cannot eventually become marketed drugs. Developing reliable computational methods for prediction of drug-likeness of candidate compounds is of vital importance to improve the success rate of drug discovery and development. In this study, we used a fully connected neural networks (FNN) to construct drug-likeness classification models with deep autoencoder to initialize model parameters. We collected datasets of drugs (represented by ZINC World Drug), bioactive molecules (represented by MDDR and WDI), and common molecules (represented by ZINC All Purchasable and ACD). Compounds were encoded with MOLD2 two-dimensional structure descriptors. The classification accuracies of drug-like/non-drug-like model are 91.04% on WDI/ACD databases, and 91.20% on MDDR/ZINC, respectively. The performance of the models outperforms previously reported models. In addition, we develop a drug/non-drug-like model (ZINC World Drug vs. ZINC All Purchasable), which distinguishes drugs and common compounds, with a classification accuracy of 96.99%. Our work shows that by using high-latitude molecular descriptors, we can apply deep learning technology to establish state-of-the-art drug-likeness prediction models.

Novel Conjugated Unsaturated Ketones with Submicromolar Potencies Towards some Leukemic and Colon Cancer Cells

BACKGROUND

Cancer continues to be the major health burden worldwide. There is an urgent need for the development of novel antineoplastic compounds to treat this devastating condition. Various alkylating anticancer drugs have been employed in the clinic for treating cancers. Unsaturated conjugated ketones are a group of alkylators which are of significant interest as potent antineoplastic agents.

OBJECTIVE

The goal of this study is to discover unsaturated conjugated ketones which are novel potent cytotoxins displaying growth-inhibitory properties towards neoplasms and also to serve as cytotoxic warheads in drug development.

METHODS

A variety of 3,5-bis (benzylidene)-4-piperidones 2a-n were synthesized and evaluated against a number of neoplastic cell lines. The short-term neurotoxicity of 2a-k, n was evaluated in mice by i.p. administration using doses level of 30, 100 and 300 mg/kg. Statistical correlations for determining structure-activity relationships were performed using an SPSS software.

RESULTS

A number of compounds display cytotoxic potencies in the region of 10-7 to 10-8 M and some of the structural features contributing to the cytotoxicity were identified. Compounds 2a-d, 2h demonstrated substantially higher cytotoxic potencies compared to melphalan and 5- fluorouracil against a panel of leukemic and colon cancer cell lines. These lead cytotoxins comply with drug-likeness properties. In general, the antineoplastics 2 are well tolerated in mice using a short-term neurotoxicity screening.

CONCLUSION

In general, this group of compounds comprises excellent cytotoxic agents, which warrant their further development as cytotoxic warheads.

Prediction Methods of Herbal Compounds in Chinese Medicinal Herbs

Chinese herbal medicine has recently gained worldwide attention. The curative mechanism of Chinese herbal medicine is compared with that of western medicine at the molecular level. The treatment mechanism of most Chinese herbal medicines is still not clear. How do we integrate Chinese herbal medicine compounds with modern medicine? Chinese herbal medicine drug-like prediction method is particularly important. A growing number of Chinese herbal source compounds are now widely used as drug-like compound candidates. An important way for pharmaceutical companies to develop drugs is to discover potentially active compounds from related herbs in Chinese herbs. The methods for predicting the drug-like properties of Chinese herbal compounds include the virtual screening method, pharmacophore model method and machine learning method. In this paper, we focus on the prediction methods for the medicinal properties of Chinese herbal medicines. We analyze the advantages and disadvantages of the above three methods, and then introduce the specific steps of the virtual screening method. Finally, we present the prospect of the joint application of various methods.

Quinolinic Carboxylic Acid Derivatives as Potential Multi-target Compounds for Neurodegeneration: Monoamine Oxidase and Cholinesterase Inhibition

BACKGROUND

Parkinson's disease (PD), a debilitating and progressive disorder, is among the most challenging and devastating neurodegenerative diseases predominantly affecting the people over 60 years of age.

OBJECTIVES

To confront PD, an advanced and operational strategy is to design single chemical functionality able to control more than one target instantaneously.

METHODS

In this endeavor, for the exploration of new and efficient inhibitors of Parkinson's disease, we synthesized a series of quinoline carboxylic acids (3a-j) and evaluated their in vitro monoamine oxidase and cholinesterase inhibitory activities. The molecular docking and in silico studies of the most potent inhibitors were performed to identify the probable binding modes in the active site of the monoamine oxidase enzymes. Moreover, molecular properties were calculated to evaluate the druglikeness of the compounds.

RESULTS

The biological evaluation results revealed that the tested compounds were highly potent against monoamine oxidase (A & B), 3c targeted both the isoforms of MAO with IC50 values of 0.51 ± 0.12 and 0.51 ± 0.03 µM, respectively. The tested compounds also demonstrated high and completely selective inhibitory action against acetylcholinesterase (AChE) with IC50 values ranging from 4.36 to 89.24 µM. Among the examined derivatives, 3i was recognized as the most potent inhibitor of AChE with an IC50 value of 4.36 ± 0.12 ±µM.

CONCLUSION

The compounds appear to be promising inhibitors and could be used for the future development of drugs targeting neurodegenerative disorders.

Synthesis, Molecular Properties Estimations, and Dual Dopamine D2 and D3 Receptor Activities of Benzothiazole-Based Ligands

Neurleptic drugs, e.g., aripiprazole, targeting the dopamine D_2S and D₃ receptors (D_2SR and D₃R) in the central nervous system are widely used in the treatment of several psychotic and neurodegenerative diseases. Therefore, a new series of benzothiazole-based ligands (3-20) was synthesized by applying the bioisosteric approach derived from the selective D₃Rs ligand BP-897 (1) and its structurally related benz[d]imidazole derivative (2). Herein, introduction of the benzothiazole moiety was well tolerated by D_2SR and D₃R binding sites leading to antagonist affinities in the low nanomolar concentration range at both receptor subtypes. However, all novel compounds showed lower antagonist affinity to D₃R when compared to that of 1. Further exploration of different substitution patterns at the benzothiazole heterocycle and the basic 4-phenylpiperazine resulted in the discovery of high dually acting D_2SR and D₃R ligands. Moreover, the methoxy substitution at 2-position of 4-phenylpiperazine resulted in significantly (22-fold) increased D_2SR binding affinity as compared to the parent ligand 1, and improved physicochemical and drug-likeness properties of ligands 3-11. However, the latter structural modifications failed to improve the drug-able properties in ligands having un-substituted 4-phenylpiperazine analogs (12-20). Accordingly, compound 9 showed in addition to high dual affinity at the D_2SR and D₃R [K_i (hD_2SR) = 2.8 ± 0.8 nM; K_i (hD₃R) = 3.0 ± 1.6 nM], promising clogS, clogP, LE (hD_2SR, hD₃R), LipE (hD_2SR, hD₃R), and drug-likeness score values of −4.7, 4.2, (0.4, 0.4), (4.4, 4.3), and 0.7, respectively. Also, the deaminated analog 10 [K_i (hD_2SR) = 3.2 ± 0.4 nM; K_i (hD₃R) = 8.5 ± 2.2 nM] revealed clogS, clogP, LE (hD_2SR, hD₃R), LipE (hD_2SR, hD₃R) and drug-likeness score values of −4.7, 4.2, (0.4, 0.4), (3.9, 3.5), and 0.4, respectively. The results observed for the newly developed benzothiazole-based ligands 3-20 provide clues for the diversity in structure activity relationships (SARs) at the D_2SR and D₃R subtypes.

Identification of potential leads against 4-hydroxytetrahydrodipicolinate synthase from Mycobacterium tuberculosis

4-hydroxy-tetrahydrodipicolinate synthase (DHDPS) is an important enzyme needed for the biosynthesis of lysine and many more key metabolites in Mycobacterium tuberculosis (Mtb). Inhibition of DHDPS is supposed to a promising therapeutic target due to its specific role in sporulation, cross-linking of the peptidiglycan polymers and biosynthesis of amino acids. In this work, a known inhibitor-based similarity search was carried out against a natural products database (Super Natural II) towards identification of more potent phyto-inhibitors. Molecular interaction studies were accomplished using three different tools to understand and establish the participation of active site residues as the key players in stabilizing the binding mode of ligands and target protein. The best phyto-compound deduced on the basis of binding affinity was further used as a template to make similarity scan across the PubChem Compound database (score > = 80 %) to get more divesred leads. In this search 5098 hits were obtained that further reduced to 262 after drug-likeness filtration. These phytochemicallike compounds were docked at the active site of DHDPS.Then, those hits selected from docking analysis that showing stronger binding and forming maximum H-bonds with the active site residues (Thr54, Thr55, Tyr143, Arg148 and Lys171). Finally, we predicted one phytochemical compound (SN00003544), two PubChem-compounds (CID41032023, CID54025334) akin to phytochemical molecule showing better interactions in comaprison of known inhibitors of target protein.These findings might be further useful to gain the structural insight into the designing of novel leads against DapA family.

Molecular Docking and Molecular Dynamics to Identify a Novel Human Immunodeficiency Virus Inhibitor from Alkaloids of Toddalia asiatica

Background:

Acquired immunodeficiency syndrome caused by human immunodeficiency virus (HIV) is an immunosuppressive disease. Over the past decades, it has plagued human health due to the grave consequences in its harness.

Objective:

For this reason, anti-HIV agents are imperative, and the search for the same from natural resources would assure the safety.

Materials and Methods:

In this investigation we have performed molecular docking, molecular property prediction, drug-likeness score, and molecular dynamics (MD) simulation to develop a novel anti-HIV drug. We have screened 12 alkaloids from a medicinal plant Toddalia asiatica for its probabilistic binding with the active site of the HIV-1-reverse transcriptase (HIV-1-RT) domain (the major contributor to the onset of the disease).

Results:

The docking results were evaluated based on free energies of binding (ΔG), and the results suggested toddanol, toddanone, and toddalenone to be potent inhibitors of HIV-1-RT. In addition, the alkaloids were subjected to molecular property prediction analysis. Toddanol and toddanone with more rotatable bonds were found to have a drug-likeness score of 0.23 and 0.11, respectively. These scores were comparable with the standard anti-HIV drug zidovudine with a model score 0.28. Finally, two characteristic protein-ligand complexes were exposed to MD simulation to determine the stability of the predicted conformations.

Conclusion:

The toddanol-RT complex showed higher stability and stronger H-bonds than toddanone-RT complex. Based on these observations, we firmly believe that the alkaloid toddanol could aid in efficient HIV-1 drug discovery.

SUMMARY

In the present study, the molecular docking and MD simulations are performed to explore the possible binding mode of HIV 1 RT with 12 alkaloids of T. asiatica. Molecular docking by AutoDock4 revealed three alkaloids toddanol, toddanone, and toddalenone with highest binding affinity towards HIV 1 RT. The drug likeness model score revealed a positive score for toddanol and toddanone which is comparable to the drug likeness score of the standard anti HIV drug zidovudine. Results from simulation analysis revealed that toddanol RT complex is more stable than toddanone RT complex inferring toddanol as a potential anti HIV drug molecule.

Abbreviations used: HIV: Human immunodeficiency virus, HIV 1 RT: HIV 1 reverse transcriptase, RNase H: Ribonuclease H, MD: Molecular dynamics, PDB: Protein databank, RMSD: Root mean square deviation, RMSF: Root mean square fluctuation.

Potential of agricultural fungicides for antifungal drug discovery

While it is true that only a small fraction of fungal species are responsible for human mycoses, the increasing prevalence of fungal diseases has highlighted an urgent need to develop new antifungal drugs, especially for systemic administration. This contribution focuses on the similarities between agricultural fungicides and drugs. Inorganic, organometallic and organic compounds can be found amongst agricultural fungicides. Furthermore, fungicides are designed and developed in a similar fashion to drugs based on similar rules and guidelines, with fungicides also having to meet similar criteria of lead-likeness and/or drug-likeness. Modern approved specific-target fungicides are well-characterized entities with a proposed structure-activity relationships hypothesis and a defined mode of action. Extensive toxicological evaluation, including mammalian toxicology assays, is performed during the whole discovery and development process. Thus modern agrochemical research (design of modern agrochemicals) comes close to drug design, discovery and development. Therefore, modern specific-target fungicides represent excellent lead-like structures/models for novel drug design and development.

Drug-likeness approach of 2-aminopyrimidines as histamine H3 receptor ligands

A small series of compounds containing derivatives of 2,4-diamino- and 2,4,6-triaminopyrimidine (compounds 2–7) was synthesized and tested for binding affinity to human histamine H₃ receptors (hH₃Rs) stably expressed in HEK-293 cells and human H₄Rs (hH₄Rs) co-expressed with Gα_i2 and Gβ₁γ₂ subunits in Sf9 cells. Working in part from the lead compound 6-(4-methylpiperazin-1-yl)-N⁴-(3-(piperidin-1-yl)propyl)pyrimidine-2,4-diamine (compound 1) with unsatisfactory affinity and selectivity to hH₃Rs, our structure-activity relationship studies revealed that replacement of 4-methylpiperazino by N-benzylamine and substitution of an amine group at the 2-position of the 2-aminopyrimidine core structure with 3-piperidinopropoxyphenyl moiety as an hH₃R pharmacophore resulted in N⁴-benzyl-N²-(4-(3-(piperidin-1-yl)propoxy)phenyl)pyrimidine-2,4-diamine (compound 5) with high hH₃R affinity (k_i =4.49±1.25 nM) and H₃R receptor subtype selectivity of more than 6,500×. Moreover, initial metric analyses were conducted based on their target-oriented drug-likeness for predictively quantifying lipophilicity, ligand efficiency, lipophilicity-dependent ligand efficiency, molecular size-independent efficiency, and topological molecular polar surface. As to the development of potential H₃R ligands, results showed that integration of the hH₃R pharmacophore in hH₄R-affine structural scaffolds resulted in compounds with high hH₃R affinity (4.5–650 nM), moderate to low hH₄R affinity (4,500–30,000 nM), receptor subtype selectivity (ratio hH₄R/hH₃R; 8–6,500), and promising calculated drug-likeness properties.

Improving the plausibility of success with inefficient metrics

To increase the probability of success in drug discovery, the concept of drug-like properties was introduced. Efficiency metrics that normalize potency against these properties could help reach drug-like space more efficiently. Potential reasons for the inefficient use of metrics and suboptimal decision making are discussed.

Design, Synthesis and Evaluation of New 2, 6-Dihydroimidazo[1, 2-c]Pyrimido[5, 4-e]-Pyrimidine-5(3H)-thiones as Possible Antihistaminic/Antiasthmatic Agents

A series of new 10-(alkylamino)-8-methyl-2, 6-dihydroimidazo[1, 2-c]pyrimido[5, 4-e]pyrimidine-5(3H)-thiones (4a-g) were subjected to molecular property prediction (drug-likeness, lipophilicity and solubility parameters) using Osiris Property Explorer, ALOGPS 2.1, Molinspiration and ACD/Chemsketch 12.0 software programmes. The calculated drug-related properties of the designed molecules were similar to those found in most marketed drugs. Amongst the proposed analogues, four promising candidates were chosen (4a-d) for synthesis on the basis of Lipinski's 'Rule of Five' and drug-likeness scores. The significant biological activity of the test compounds in two in vitro modes (isolated guinea pig tracheal chain preparation, isolated guinea pig ileum) supports the promise and accuracy of the prediction. Among them, 4a was the most potent antihistaminic (IC50 value of 30.2 μM; standard, chlorpheniramine maleate showed an IC50 of 14.1 μM).

Synthesis, molecular properties prediction, and anti-staphylococcal activity of N-acylhydrazones and new 1,3,4-oxadiazole derivatives

Five new 1-(2-(5-nitrofuran-2-yl)-5-(aryl)-1,3,4-oxadiazol-3-(2H)-yl) ethanone compounds 5a-e were synthesized by cyclization of N-acylhydrazones 4a-e with acetic anhydride under reflux conditions. Their structures were fully characterized by IR, ¹H-NMR, and ¹³C-NMR. Furthermore, evaluations of the antibacterial activity of the 1,3,4-oxadiazoles 5a-e and N-acylhydrazones 4a-e showed strong activity against several strains of Staphylococcus aureus, with MICs between 4 μg/mL to 32 μg/mL. In silico studies of the parameters of Lipinski's Rule of Five, as well as the topological polar surface area (TPSA), absorption percentage (% ABS), drug likeness and drug score indicate that these compounds, especially 4a and 5d, have potential to be new drug candidates.

Synthetic Medicinal Chemistry in Chagas' Disease: Compounds at The Final Stage of "Hit-To-Lead" Phase

Chagas' disease, or American trypanosomosiasis, has been the most relevant illness produced by protozoa in Latin America. Synthetic medicinal chemistry efforts have provided an extensive number of chemodiverse hits at the "active-to-hit" stage. However, only a more limited number of these have been studied in vivo in models of Chagas' disease. Herein, we survey some of the cantidates able to surpass the "hit-to-lead" stage discussing their limitations or merit to enter in clinical trials in the short term.