Synthesis of novel 5-HT1A arylpiperazine ligands: Binding data and computer-aided analysis of pharmacological potency

Serotonin receptors modulate numerous behavioral and neuropsychological processes. Therefore, they are the target for the action of many drugs, such as antipsychotics, antidepressants, antiemetics, migraine remedies, and many others. The 5-HT1A receptors have been involved in the pathogenesis and treatment of anxiety and depression and represent a promising target for new drugs with reduced extrapyramidal side effects. In most antidepressants, a piperazine-based structural motif can be identified as a common moiety. Here we describe the synthesis, pharmacological, and in silico characterization of a novel arylpiperazines series with excellent 5-HT1A affinity. The final compounds, 4a, 8a, and 8b, were selected according to predictions of in silico pharmacokinetics, docking analysis, and molecular dynamics in conjunction with physical properties, and metabolic stability. The accentuated molecules could serve as a lead compound for developing 5-HT1A drug-like molecules for depression treatment.     

Identification of potential inhibitors against nuclear Dam1 complex subunit Ask1 of Candida albicans using virtual screening and MD simulations

Identification of hit compounds against specific target form the starting point for a drug discovery program. A consistent decline of new chemical entities (NCEs) in recent years prompted a challenge to explore newer approaches to discover potential hit compounds that in turn can be converted into leads, and ultimately drug with desired therapeutic efficacy. The vast amount of omics and activity data available in public databases offers an opportunity to identify novel targets and their potential inhibitors. State of the art in silico methods viz., clustering of compounds, virtual screening, molecular docking, MD simulations and MMPBSA calculations were employed in a pipeline to identify potential ‘hits’ against those targets as well whose structures, as of now, could only predict through threading approaches. In the present work, we have started from scratch, amino acid sequence of target and compounds retrieved from PubChem compound database, modeled it in such a way that led to the identification of possible inhibitors of Dam1 complex subunit Ask1 of Candida albicans. We also propose a ligand based binding site determination approach. We have identified potential inhibitors of Ask1 subunit of a Dam1 complex of C. albicans, which is required to prevent precocious spindle elongation in pre-mitotic phases. The proposed scheme may aid to find virtually potential inhibitors of other unique targets against candida.     

Design,Synthesis, and Biological Evaluation of 3,5‐Disubstituted 2‐Pyrazineamide Derivatives as Antitubercular Agents

A novel series of 3,5‐disubstituted‐2‐pyrazineamide derivatives ( 5a–5o ) were synthesized and studied for their potential as antitubercular agents. Among them, the compounds 5a , 5g , and 5m showed the good minimal inhibitory concentration of 20, 25, and 25 μg/mL, respectively. The compound 5a displayed excellent minimum inhibitory concentration of 10 μg/mL and is four times more potent compared with the standard drug, rifampicin concentration. In silico docking studies revealed that the compounds 5a and 5c can bind strongly in the active site of 2FUM enzyme and prevent enzyme–substrate interactions. In addition, in silico docking studies were calculated, and based on the data obtained, compound 5a displayed excellent drug‐like properties.     

Sub-structure-based screening and molecular docking studies of potential enteroviruses inhibitors

Rhinoviruses (RV), especially Human rhinovirus (HRVs) have been accepted as the most common cause for upper respiratory tract infections (URTIs). Pleconaril, a broad spectrum anti-rhinoviral compound, has been used as a drug of choice for URTIs for over a decade. Unfortunately, for various complications associated with this drug, it was rejected, and a replacement is highly desirable. In silico screening and prediction methods such as sub-structure search and molecular docking have been widely used to identify alternative compounds. In our study, we have utilised sub-structure search to narrow down our quest in finding relevant chemical compounds. Molecular docking studies were then used to study their binding interaction at the molecular level. Interestingly, we have identified 3 residues that is worth further investigation in upcoming molecular dynamics simulation systems of their contribution in stable interaction.     

Synthesis,pharmacological evaluation,and molecular modeling studies of novel isatin hybrids as potential anticancer agents

A novel series of isatin hybrids 5a-g was designed, synthesized, and characterized spectroscopically. The synthesized compounds were evaluated for their cytotoxic activity against the human breast cancer cell line (MCF-7) by in vitro MTT assay. Amongst the tested compounds, 5e compound bearing benzyl moiety at N₄ piperazine was found to be the most active with the promising IC₅₀ (12.47 µM). Moreover, the active compounds 5e and 5g were subjected to antitumor evaluation (in vivo) against Dalton’s ascitic lymphoma (DAL) cell line and the results suggested that the best active compound 5e can normalize the blood picture in comparison to the standard drug. An in silico molecular docking study using the crystal structure of Hsp90 protein described the role of significant protein–ligand interactions and revealed more insights into the binding mode. The drug-likeliness of the compounds was predicted based on Lipinski's rule of five and pharmacokinetic ADME parameters. Hence, the synthesized isatin hybrids could be novel starting point anticancer lead compounds demonstrating drug-like properties which can be explored further for anticancer drug discovery.     

Antibacterial potential of N-(2-furylmethylidene)-1, 3, 4-thiadiazole-2-amine: Experimental and theoretical investigations

Recently, a lot of interest has been attributed to the Schiff base compound because of its wide range of biological activities which include: antibacterial, antifungal, antima larial, including; antiproliferative, antiviral, and antipyretic. In this research work, N-(2-furylmethylidene)-1, 3, 4-thiadiazole- 2-amine gotten from o-phenylenediamine and 5- methoxysalicaldehyde was produced and characterized using UV–Visible, FT-IR, ¹H NMR, ¹³C NMR, and GC-MS along with molecular modeling using density functional theory (DFT) and molecular docking approach. The results obtained indicated that the Schiff base exhibited antimicrobial action against all the tested microbes except Candidaalbicans isolate, which exhibited zero diameter zone of inhibition. The theoretical investigations of the synthesized compounds were computed applying density functional theory at the B3LYP/6–31++G (d, p) level of theory and in silico molecular docking simulation. In comparing binding affinity energies and binding poses of the studied compound and the standard drug (ampicillin), the deduction that the molecular docking analysis results are in good agreement with in vitro analysis of the synthesized compounds can be made.     

Molecular modeling and structural analysis of some tetrahydroindazole and cyclopentanepyrazole derivatives as COX-2 inhibitors

In an attempt to rationalize the search for new potential anti-inflammatory compounds on the COX-2 enzyme, we carried out an in silico protocol that successfully combines the prediction of physicochemical and pharmacokinetic properties, molecular docking, molecular dynamic simulation, and free energy calculation. Starting from a small library of compounds synthesized previously, it was found that 70% of the compounds analyzed satisfy with the associated values to physicochemical principles as key evaluation parameters for the drug-likeness; all the compounds presented good gastrointestinal absorption and cerebral permeability and they showed an interaction with the Arg 106 residue of the COX-2 isoenzyme. Finally, it was obtained that compound 3ab has a binding mode, binding energy, and stability in the active site of COX-2 like the reference drug celecoxib, suggesting that this compound could become a powerful candidate in the inhibition of the COX-2 enzyme. In addition, we realized the crystallographic analysis of compounds 3j, 3r, and 3t defining the crystal parameters and the Packing interactions.     

Identification of potential inhibitor and enzyme-inhibitor complex on trypanothione reductase to control Chagas disease

Chagas is a parasitic disease with major threat to public health due to its resistance against commonly available drugs. Trypanothione reductase (TryR) is the key enzyme to develop this disease. Though this enzyme is well thought-out as potential drug target, the accurate structure of enzyme-inhibitor complex is required to design a potential inhibitor which is less available for TryR. In this research, we aimed to investigate the advanced drug over the available existing drugs by designing inhibitors as well as to identify a new enzyme-inhibitor complex that may act as a template for drug design. A set of analogues were designed from a known inhibitor Quinacrine Mustard (QUM) to identify the effective inhibitor against this enzyme. Further, the pharmacoinformatics elucidation and structural properties of designed inhibitor proposed effective drug candidates against Chagas disease. Molecular docking study suggests that a designed inhibitor has higher binding affinity in both crystal and modeled TryR and also poses similar interacting residues as of crystal TryR-QUM complex structure. The comparative studies based on in silico prediction proposed an enzyme-inhibitor complex which could be effective to control the disease activity. So our in silico analysis based on TryR built model, Pharmacophore and docking analysis might play an important role for the development of novel therapy for Chagas disease. But both animal model experiments and clinical trials must be done to confirm the efficacy of the therapy.     

Prediction of COVID-19 manipulation by selective ACE inhibitory compounds of Potentilla reptant root: In silico study and ADMET profile

In the novel SARS-CoV-2 (COVID-19) as a global emergency event, the main reason of the cardiac injury from COVID-19 is angiotensin-converting enzyme 2 (ACE2) targeting in SARS-CoV-2 infection. The inhibition of ACE2 induces an increase in the angiotensin II (Ang II) and the angiotensin II receptor type 1 (AT1R) leading to impaired cardiac function or cardiac inflammatory responses. The ethyl acetate fraction of Potentilla reptans L. root can rescue heart dysfunction, oxidative stress, cardiac arrhythmias and apoptosis. Therefore, isolated components of P. reptans evaluated to identify natural anti-SARS-CoV-2 agents via molecular docking.In silico molecular docking study were carried out using the Auto Dock software on the isolated compounds of Potentilla reptans root. The protein targets of selective ACE and others obtained from Protein Data Bank (PDB). The best binding pose between amino acid residues involved in active site of the targets and compounds was discovered via molecular docking. Furthermore, ADMET properties of the compounds were evaluated.The triterpenoids of P. reptans showed more ACE inhibitory potential than catechin in both domains. They were selective on the nACE domain, especially compound 5. Also, the compound 5 & 6 had the highest binding affinity toward active site of nACE, cACE, AT1R, ACE2, and TNF-α receptors. Meanwhile, compound 3 showed more activity to inhibit TXA2. Drug likeness and ADMET analysis showed that the compounds passed the criteria of drug likeness and Lipinski rules. The current study depicted that P. reptans root showed cardioprotective effect in COVID-19 infection and manipulation of angiotensin II-induced side effects.     

Prediction of African Swine Fever Virus Inhibitors by Molecular Docking-Driven Machine Learning Models

African swine fever virus (ASFV) causes a highly contagious and severe hemorrhagic viral disease with high mortality in domestic pigs of all ages. Although the virus is harmless to humans, the ongoing ASFV epidemic could have severe economic consequences for global food security. Recent studies have found a few antiviral agents that can inhibit ASFV infections. However, currently, there are no vaccines or antiviral drugs. Hence, there is an urgent need to identify new drugs to treat ASFV. Based on the structural information data on the targets of ASFV, we used molecular docking and machine learning models to identify novel antiviral agents. We confirmed that compounds with high affinity present in the region of interest belonged to subsets in the chemical space using principal component analysis and k-means clustering in molecular docking studies of FDA-approved drugs. These methods predicted pentagastrin as a potential antiviral drug against ASFVs. Finally, it was also observed that the compound had an inhibitory effect on AsfvPolX activity. Results from the present study suggest that molecular docking and machine learning models can play an important role in identifying potential antiviral drugs against ASFVs.     

Identification of Potential Inhibitors of MurD Enzyme of Staphylococcus aureus from a Marine Natural Product Library

Staphylococcus aureus is an opportunistic pathogen that can cause fatal bacterial infections. MurD catalyzes the formation of peptide bond between UDP-N-acetylehyl-l-alanine and d-glutamic acid, which plays an important role in the synthesis of peptidoglycan and the formation of cell wall by S. aureus. Because S. aureus is resistant to most existing antibiotics, it is necessary to develop new inhibitors. In this study, Schrodinger 11.5 Prime homology modeling was selected to prepare the protein model of MurD enzyme, and its structure was optimized. We used a virtual screening program and similarity screening to screen 47163 compounds from three marine natural product libraries to explore new inhibitors of S. aureus. ADME provides analysis of the physicochemical properties of the best performing compounds during the screening process. To determine the stability of the docking effect, a 100 ns molecular dynamics was performed to verify how tightly the compound was bound to the protein. By docking analysis and molecular dynamics analysis, both 46604 and 46608 have strong interaction with the docking pocket, have good pharmacological properties, and maintain stable conformation with the target protein, so they have a chance to become drugs for S. aureus. Through virtual screening, similarity screening, ADME study and molecular dynamics simulation, 46604 and 46608 were selected as potential drug candidates for S. aureus.     

In silico exploration of anti-Alzheimer's compounds present in methanolic extract of Neolamarckia cadamba bark using GC–MS/MS

Alzheimer’s disease (AD) can be treated by the inhibition of Beta Amyloid protein (Aβ) and inhibition of Acetylcholinesterase (ACHE). Anti-Alzheimer’s potential phytoconstituents from Neolamarckia cadamba methanolic bark extracts were identified through GC–MS/MS analysis and in silico molecular docking analysis. Powdered bark sample was subjected to extract by soxhlet extractor with n-hexane, chloroform and methanol solvents respectively. The methanolic extract was taken for GC–MS/MS analysis, the observed chromatogram was revealed the presence of 61 constituents in the methanolic extract, 59 new phytoconstituents were identified which were not reported earlier as constituents any part of N. cadamba. GC–MS/MS detected phytoconstituents were analysed through the docking analysis by iGEMDOCK software against Aβ (PDB ID: 2LMN) and ACHE (PDB ID: 3LII) and compared with standard known inhibitors of galantamine and curcumin. Docking analysis binding energy was determined and verified by Discovery studio visulaizer. Both inhibition assay top 5 best dock energy compounds were analysed through the in silico modeling through admetSAR web portal for parameters of intestinal absorption, blood brain barrier permeation, carcinogencity, and acute oral toxicity were determined. From that heptadecanoic acid, 16-methyl-, methyl ester; beta-sitosterol acetate and octadecanoic acid, 2-hydroxy-, methyl ester inhibitors were identified. Further the top lead successful compound of each target molecular interactions were detected by LigPlot analysis. From this research these three compounds are best to treat AD than standard. Isolation of individual compounds would, however, help to find new compounds for other diseases and lead molecules for AD were identified.     

In silico modeling and molecular docking insights of kaempferitrin for colon cancer-related molecular targets

Colorectal cancer is one of the most common cancers worldwide, and it is also one of the major causes of mortality from cancer. Chemotherapy drugs are generally limited due to various complications, as well as the development of resistance and recurrence. The in silico docking investigation involved exploration of protein or nucleotide, 3D structural modeling, molecular docking, and binding energy calculation. Protein-protein interactions are significant to many biological processes, and their disruption is a leading cause of disease. The use of small molecules to modulate them is gaining popularity, but protein interfaces usually lack specific cavities for processing small molecules. MMP-2, PARP, iNOS, Chk1, proteins were used in the molecular docking analysis of kaempferitrin and 5-flurouracil. The compound kaempferitrin had the highest binding energy scores with most of the target proteins, according to molecular docking results. The findings suggest it could be used to develop new drugs for cancer therapy.     

Molecular docking studies of some new imidazole derivatives for antimicrobial properties

In modern drug designing, molecular docking is routinely used for understanding drug-receptor interaction. In the present study six imidazole derivatives containing substituted pyrazole moiety (2a,b and 4a–d) were synthesized. Structures of the newly synthesized compounds were characterized by spectral studies. Compounds were screened for their antibacterial activity. Compound 4c was found to be potent antimicrobial against Pseudomonas aeruginosa at concentrations of 1 and 0.5 mg/mL compared to standard drug Streptomycin. All the compounds were subjected to molecular docking studies for the inhibition of the enzyme l-glutamine: d-fructose-6-phosphate amidotransferase[GlcN-6-P] (EC 2.6.1.16). The in silico molecular docking study results showed that, all the synthesized compounds having minimum binding energy and have good affinity toward the active pocket, thus, they may be considered as good inhibitor of GlcN-6-P synthase.     

Evaluation of drug candidature: In silico ADMET,binding interactions with CDK7 and normal cell line studies of potentially anti-breast cancer enamidines

We have recently explored novel class of potentially anti-breast cancer active enamidines in which four molecules 4a-c and 4h showed higher anticancer activity compared to standard drug doxorubicin. As a part of extension of this work, we have further evaluated in silico cheminformatic studies on bioactivity prediction of synthesized series of enamidines using mole information. The normal cell line study of four lead compounds 4a-c and 4h against African green monkey kidney vero strain further revealed that the compounds complemented good selectivity in inhibition of cancer cells. The in silico bioactivity and molecular docking studies also revealed that the compounds have significant interactions with the drug targets. The results reveal that enamidine moieties are vital for anti-breast cancer activity as they possess excellent drug-like characteristics, being potentially good inhibitors of cyclin dependent kinases7 (CDK7).     

DG-AMMOS: A New tool to generate 3D conformation of small molecules using Distance Geometry and Automated Molecular Mechanics Optimization for in silico Screening

Background  

Discovery of new bioactive molecules that could enter drug discovery programs or that could serve as chemical probes is a very complex and costly endeavor. Structure-based and ligand-based in silico screening approaches are nowadays extensively used to complement experimental screening approaches in order to increase the effectiveness of the process and facilitating the screening of thousands or millions of small molecules against a biomolecular target. Both in silico screening methods require as input a suitable chemical compound collection and most often the 3D structure of the small molecules has to be generated since compounds are usually delivered in 1D SMILES, CANSMILES or in 2D SDF formats.     

In silico identification of natural products with anticancer activity using a chemo-structural database of Brazilian biodiversity

Cancer is one of the leading causes of death worldwide, and the number of patients has only increased each year, despite the considerable efforts and investments in scientific research. Since natural products (NPs) may serve as suitable sources for drug development, the cytotoxicity against cancer cells of 2221 compounds from the Nuclei of Bioassays, Ecophysiology, and Biosynthesis of Natural Products Database (NuBBE_DB) was predicted using CDRUG algorithm. Molecular modeling, chemoinformatics, and chemometric tools were then used to analyze the structural and physicochemical properties of these compounds. We compared the positive NPs with FDA-approved anticancer drugs and predicted the molecular targets involved in the anticancer activity. In the present study, 46 families comprising potential anticancer compounds and at least 19 molecular targets involved in oncogenesis. To the best of our knowledge, this is the first large-scale study conducted to evaluate the potentiality of NPs sourced from Brazilian biodiversity as anticancer agents, using in silico approaches. Our results provided interesting insights about the mechanism of action of these compounds, and also suggested that their structural diversity may aid structure-based optimization strategies for developing novel drugs for cancer therapy.     

3D-QSAR,docking, molecular dynamics simulation and free energy calculation studies of some pyrimidine derivatives as novel JAK3 inhibitors

Janus kinase 3 (JAK3) is a promising drug target for the treatment of inflammatory diseases, autoimmune disorders, organ transplant rejection and various cancers. In the present study, 3D-QSAR, docking, MD simulation and MM/PBSA studies were performed on a series of pyrimidine-based JAK3 inhibitors. A reliable COMSIA (q² = 0.717 and r² = 0.986) model was developed and validated using external validation test set, bootstrapping, progressive scrambling and r_m² metrics analyses. Structural requirements identified through contour maps of the model were strategically utilized to computationally design 170 novel JAK3 inhibitors with improved potency. Docking studies were performed on the selected data set and newly designed compounds to show their binding mode and to identify important interacting residues inside the active site of JAK3. In addition, docking results of the selected designed compounds inside the active sites of JAK1, JAK2 and TYK2 indicated their JAK3 selectivity. MD simulation (100 ns) on the docked complex of compound 28 (one of highly active compounds of the data set) assisted in the further exploration of the binding interactions. Some crucial residues like Lys830 (glycine-rich loop), Val836, Ala853, Leu905 (hinge region), Cys909, Asn954, Leu956 and Ala966 were identified. Hydrogen bond interactions with hinge residue Leu905 were critical for the binding of JAK3 inhibitors. Additionally, MM/PBSA calculation provided the binding free energy of the compound 28. Newly designed molecules showed promising results in the preliminary in silico ADMET evaluations. Outcomes of the study can further be exploited to develop potent JAK3 inhibitors.     

Computer-Assisted Design of New Drugs Based on Retrometabolic Concepts

Abstract

Retrometabolic drug design approaches incorporate metabolic and toxicological considerations into the drug design process and represent a novel, systematic methodology for the design of safe compounds. Two major design concepts aimed to increase the therapeutic index (the activity/toxicity ratio) of drugs were developed. Chemical delivery systems (CDS) are primarily used to allow targeting of the active biological molecules to specific target sites or organs based on predictable enzymatic activation. Soft drug approaches are used to design new drugs by building in the molecule, in addition to the activity, the most desired way in which the molecule is to be deactivated and detoxified subsequent to exerting its biological effects. Special computer programs were developed that starting from a lead compound generate complete libraries of possible soft analogs and then help ranking these candidates based on isosteric-isoelectronic comparisons, predicted solubility/partition properties, and estimated metabolic rates. The novel field of large peptide-CDSs imposes special challenges, but a new, remarkably simple model was developed to estimate partition properties for a wide range of compounds, including quite large peptide derivatives. A suggested change of about five order of magnitudes in the distribution coefficient can explain the “lock in” mechanism of brain-targeting delivery systems.