Molecular dynamics simulation and binding free energy studies of novel leads belonging to the benzofuran class inhibitors of Mycobacterium tuberculosis Polyketide Synthase 13

Structural and mechanistic insights into Quinolone Synthase to address its functional promiscuity

Quinolone synthase from Aegle marmelos (AmQNS) is a type III polyketide synthase that yields therapeutically effective quinolone and acridone compounds. Addressing the structural and molecular underpinnings of AmQNS and its substrate interaction in terms of its high selectivity and specificity can aid in the development of numerous novel compounds. This paper presents a high-resolution AmQNS crystal structure and explains its mechanistic role in synthetic selectivity. Additionally, we provide a model framework to comprehend structural constraints on ketide insertion and postulate that AmQNS's steric and electrostatic selectivity plays a role in its ability to bind to various core substrates, resulting in its synthetic diversity. AmQNS prefers quinolone synthesis and can accommodate large substrates because of its wide active site entrance. However, our research suggests that acridone is exclusively synthesized in the presence of high malonyl-CoA concentrations. Potential implications of functionally relevant residue mutations were also investigated, which will assist in harnessing the benefits of mutations for targeted polyketide production. The pharmaceutical industry stands to gain from these findings as they expand the pool of potential drug candidates, and these methodologies can also be applied to additional promising enzymes.

A DFT study of sulforaphane adsorption on the group III nitrides (B12N12, Al12N12 and Ga12N12) nanocages

In this paper, the adsorption behavior of group III nitrides (B12N12, Al12N12, and Ga12N12) nanocages to sulforaphane (SF) anticancer medicine were studied by density functional theory (DFT). The adsorption energy, solvation energy, desorption time and related quantum molecular descriptors were calculated in neutral and acidic solutions. When the drugs were adsorbed to nanocages, the structure of nanocages and drugs changed after adsorption, indicating that the process was effective adsorption. The adsorption energy and solvation energy of the complexes created after adsorption were negative values, which indicated that the structure of complexes formed by adsorption were stable. According to charge decomposition analysis (CDA) and natural bonding orbitals (NBO), drugs act as charge donors and nanocages act as charge acceptors, so that the charge flows from drugs to nanocages. Thermodynamic calculations demonstrate that drugs adsorption on nanocages is a spontaneous exothermic process. The calculation of quantum molecular descriptors confirmed that drugs adsorption on nanocages increased the chemical reactivity and solubility of drugs, which facilitated its transfer in biological fluids. Both interaction region index (IRI) and topological analysis of atom in molecule (AIM) revealed Van Der Waals interaction between drugs and nanocages. Protonation studies demonstrated that acidic circumstances could improve the polarity of complexes, increase the solvation effect, and boost drugs release in target cancer cells. The results of this work indicate that X12N12(X = B, Al, Ga) nanocages can be used as the delivery vehicle of SF drug.Communicated by Ramaswamy H. Sarma.

Design and Identification of Inhibitors for the Spike-ACE2 Target of SARS-CoV-2

When an epidemic started in the Chinese city of Wuhan in December 2019, coronavirus was identified as the cause. Infection by the virus occurs through the interaction of viral S protein with the hosts' angiotensin-converting enzyme 2. By leveraging resources such as the DrugBank database and bioinformatics techniques, ligands with potential activity against the SARS-CoV-2 spike protein were designed and identified in this investigation. The FTMap server and the Molegro software were used to determine the active site of the Spike-ACE2 protein's crystal structure. Virtual screening was performed using a pharmacophore model obtained from antiparasitic drugs, obtaining 2000 molecules from molport^®. The ADME/Tox profiles were used to identify the most promising compounds with desirable drug characteristics. The binding affinity investigation was then conducted with selected candidates. A molecular docking study showed five structures with better binding affinity than hydroxychloroquine. Ligand_003 showed a binding affinity of -8.645 kcal·mol^-1, which was considered an optimal value for the study. The values presented by ligand_033, ligand_013, ligand_044, and ligand_080 meet the profile of novel drugs. To choose compounds with favorable potential for synthesis, synthetic accessibility studies and similarity analyses were carried out. Molecular dynamics and theoretical IC₅₀ values (ranging from 0.459 to 2.371 µM) demonstrate that these candidates are promising for further tests. Chemical descriptors showed that the candidates had strong molecule stability. Theoretical analyses here show that these molecules have potential as SARS-CoV-2 antivirals and therefore warrant further investigation.

Advances in computational frameworks in the fight against TB: The way forward

Around 1.6 million people lost their life to Tuberculosis in 2021 according to WHO estimates. Although an intensive treatment plan exists against the causal agent, Mycobacterium Tuberculosis, evolution of multi-drug resistant strains of the pathogen puts a large number of global populations at risk. Vaccine which can induce long-term protection is still in the making with many candidates currently in different phases of clinical trials. The COVID-19 pandemic has further aggravated the adversities by affecting early TB diagnosis and treatment. Yet, WHO remains adamant on its "End TB" strategy and aims to substantially reduce TB incidence and deaths by the year 2035. Such an ambitious goal would require a multi-sectoral approach which would greatly benefit from the latest computational advancements. To highlight the progress of these tools against TB, through this review, we summarize recent studies which have used advanced computational tools and algorithms for-early TB diagnosis, anti-mycobacterium drug discovery and in the designing of the next-generation of TB vaccines. At the end, we give an insight on other computational tools and Machine Learning approaches which have successfully been applied in biomedical research and discuss their prospects and applications against TB.

Revealing the drug resistance mechanism of saquinavir due to G48V and V82F mutations in subtype CRF01_AE HIV-1 protease: molecular dynamics simulation and binding free energy calculations

Human immunodeficiency virus-1 (HIV-1) protease is one of the important targets in AIDS therapy. The majority of HIV infections are caused due to non-B subtypes in developing countries. The co-occurrence of mutations along with naturally occurring polymorphisms in HIV-1 protease cause resistance to the FDA approved drugs, thereby posing a major challenge in the treatment of antiretroviral therapy. In this work, the resistance mechanism against SQV due to active site mutations G48V and V82F in CRF01_AE (AE) protease was explored. The binding free energy calculations showed that the direct substitution of valine at position 48 introduces a bulkier side chain, directly impairing the interaction with SQV in the binding pocket. Also, the intramolecular hydrogen bonding network of the neighboring residues is altered, indirectly affecting the binding of SQV. Interestingly, the substitution of phenylalanine at position 82 induces conformational changes in the 80's loop and the flap region, thereby favoring the binding of SQV. The V82F mutant structure also maintains similar intramolecular hydrogen bond interactions as observed in AE-WT.Communicated by Ramaswamy H. Sarma.

The effect of C/N ratio and its frequent addition on commensal and pathogenic bacterial abundances in shrimp Litopeaneus vanname gut in a biofloc system: Ratio and frequent addition interaction matters

The environmental biotic and abiotic factors form a complicated relationship with the host intestinal microbiota. In our study, we applied different levels of C/N ratio (10, 15, 20) and frequent addition times (once, twice, triple a day) in a factorial experimental design. GC/LC analysis of filtrated biofloc (BF) samples revealed the highest relative fold change for the untargeted bioactive molecules among different treatments, whereas the 16s rRNA analysis revealed the change in the shrimp gut microbiota composition. Based on the available literature on the relationship between the bioactive molecules and the available bacteria in this study, the next bioactive molecules were discussed. Proline was associated with Bacteroidota, Flavobacteriaceae, Gammaproteobacteria, and Flavobacteriales. Plumbagine was associated with Norcardiaceae. Phytosphingosin was associated with Bacteroidota. Phosphocholine compound was associated with Bacteroidota. The monobutyl ether, benzofuran, and piperidone were associated with Micobacteriaceae and Mycobacterium. Generally, C/N 15 and 20 once a day, and C/N 20 triple a day have showed a merit over other treatments in term of low pathogenic and unfavorable bacteria, and high commensal bacterial abundances. The revealed bioactive molecule composition showed the complicity of BF as a source for novel compounds as biosecurity agents in BF system. These molecules could be developed to feed additives upgrading the biosecurity level in aquaculture systems. Other bioactive molecules require future studies to reveal novel molecules in term of aquaculture biosecurity control.

Identification of novel inhibitors for mycobacterial polyketide synthase 13 via in silico drug screening assisted by the parallel compound screening with genetic algorithm-based programs

Identifying small compounds capable of inhibiting Mycobacterium tuberculosis polyketide synthase 13 (Pks13), in charge of final step of mycolic acid biosynthesis, could lead to the development of a novel antituberculosis drug. This study screened for lead compounds capable of targeting M. tuberculosis Pks13 from a chemical library comprising 154,118 compounds through multiple in silico docking simulations. The parallel compound screening (PCS), conducted via two genetic algorithm-based programs was applied in the screening strategy. Out of seven experimentally validated compounds, four compounds showed inhibitory effects on the growth of the model mycobacteria (Mycobacterium smegmatis). Subsequent docking simulation of analogs of the promising leads with the assistance of PCS resulted in the identification of three additional compounds with potent antimycobacterial effects (compounds A1, A2, and A5). Further, molecular dynamics simulation predicted stable interaction between M. tuberculosis Pks13 active site and compound A2, which showed potent antimycobacterial activity comparable to that of isoniazid. The present study demonstrated the efficacy of in silico structure-based drug screening through PCS in antituberculosis drug discovery.

Virtual Screening of Natural Chemical Databases to Search for Potential ACE2 Inhibitors

The angiotensin-converting enzyme II (ACE2) is a multifunctional protein in both health and disease conditions, which serves as a counterregulatory component of RAS function in a cardioprotective role. ACE2 modulation may also have relevance to ovarian cancer, diabetes, acute lung injury, fibrotic diseases, etc. Furthermore, since the outbreak of the coronavirus disease in 2019 (COVID-19), ACE2 has been recognized as the host receptor of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The receptor binding domain of the SARS-CoV-2 S-protein has a strong interaction with ACE2, so ACE2 may be a potent drug target to prevent the virus from invading host cells for anti-COVID-19 drug discovery. In this study, structure- and property-based virtual screening methods were combined to filter natural product databases from ChemDiv, TargetMol, and InterBioScreen to find potential ACE2 inhibitors. The binding affinity between protein and ligands was predicted using both Glide SP and XP scoring functions and the MM-GBSA method. ADME properties were also calculated to evaluate chemical drug-likeness. Then, molecular dynamics (MD) simulations were performed to further explore the binding modes between the highest-potential compounds and ACE2. Results showed that the compounds 154-23-4 and STOCK1N-07141 possess potential ACE2 inhibition activities and deserve further study.

In silico discovery of novel inhibitors from Northern African natural products database against main protease (Mpro) of SARS-CoV-2

The recent outbreak of COVID-19 (Coronavirus Disease 2019), caused by a novel SARS-CoV-2 virus, has led to public health emergencies worldwide where time is as important as equipment to save lives. Antimalarial drugs such as hydroxychloroquine and chloroquine derivatives are used in emergencies but they are not suitable for patients with high blood pressure, diabetes and heart problems. Since there are no approved drugs for this disease, science is challenged to find vaccines and new drugs. Therefore, as part of our Silico drug design strategy, we identified drug-like compounds that inhibit replication of the main protease (Mpro) of SARS-CoV-2 based on receptor-based virtual database screening, molecular docking, molecular dynamics, and drug-similarity profiling from the NANPDB natural products database available at North African. The two resulting hit compounds named 5- Chloro-Omega-hydroxy-1-O-methylemodin and cystodion E showed the highest binding energy with Mpro of SARS-CoV-2 and strong inhibitory activity compared with the previously published N3 inhibitor. The complexes of these two compounds were validated by molecular dynamics analysis (RMSD, RMSF, Rg, total number of hydrogen bonds and secondary structure fractions of the protein in the complex) as the best method to evaluate the biological stability of the system. Therefore, these molecules deserve more attention in drug development compared to COVID-19. HighlightsA large database of natural compounds was screened against nCoV-2's Mpro.Molecular docking and Molecular dynamics were used as powerful methods.Two compounds were found are very attractive to inhibit Mpro of nCoV-2.ADME-Tox profiling is evaluated the active compounds are not cancerogenic.Communicated by Ramaswamy H. Sarma.

Spike protein recognizer receptor ACE2 targeted identification of potential natural antiviral drug candidates against SARS-CoV-2

Angiotensin-converting enzyme 2 (ACE2), also known as peptidyl-dipeptidase A, belongs to the dipeptidyl carboxydipeptidases family has emerged as a potential antiviral drug target against SARS-CoV-2. Most of the ACE2 inhibitors discovered till now are chemical synthesis; suffer from many limitations related to stability and adverse side effects. However, natural, and selective ACE2 inhibitors that possess strong stability and low side effects can be replaced instead of those chemicals' inhibitors. To envisage structurally diverse natural entities as an ACE2 inhibitor with better efficacy, a 3D structure-based-pharmacophore model (SBPM) has been developed and validated by 20 known selective inhibitors with their correspondence 1166 decoy compounds. The validated SBPM has excellent goodness of hit score and good predictive ability, which has been appointed as a query model for further screening of 11,295 natural compounds. The resultant 23 hits compounds with pharmacophore fit score 75.31 to 78.81 were optimized using in-silico ADMET and molecular docking analysis. Four potential natural inhibitory molecules namely D-DOPA (Amb17613565), L-Saccharopine (Amb6600091), D-Phenylalanine (Amb3940754), and L-Mimosine (Amb21855906) have been selected based on their binding affinity (−7.5, −7.1, −7.1, and −7.0 kcal/mol), respectively. Moreover, 250 ns molecular dynamics (MD) simulations confirmed the structural stability of the ligands within the protein. Additionally, MM/GBSA approach also used to support the stability of molecules to the binding site of the protein that also confirm the stability of the selected four natural compounds. The virtual screening strategy used in this study demonstrated four natural compounds that can be utilized for designing a future class of potential natural ACE2 inhibitor that will block the spike (S) protein dependent entry of SARS-CoV-2 into the host cell.

Hormones Nanofiltration in Carbon Nanotubes and Boron Nitride Nanotubes Using Uniform External Electric Field Through Molecular Dynamics

Hormones are a dangerous group of molecules that can cause harm to humans. This study based on classical molecular dynamics proposes the nanofiltration of wastewater contaminated by hormones from a computer simulation study, in which the water and the hormone were filtered in two single-walled nanotube compositions. The calculations were carried out by changing the intensities of the electric field that acted as a force exerting pressure on the filtration along the nanotube, in the simulation time of 100 ps. The hormones studied were estrone, estradiol, estriol, progesterone, ethinylestradiol, diethylbestrol, and levonorgestrel in carbon nanotubes (CNTs) and boron nitride (BNNTs). The most efficient nanofiltrations were for fields with low intensities in the order of 10-8 au and 10-7 au. The studied nanotubes can be used in membranes for nanofiltration in water treatment plants due to the evanescent field potential caused by the action of the electric field inside. Our data showed that the action of EF in conjunction with the van der Walls forces of the nanotubes is sufficient to generate the attractive potential. Evaluating the transport of water molecules in CNTs and BNNTs, under the influence of the electric field, a sequence of simulations with the same boundary conditions was carried out, seeking to know the percentage of water molecules filtered in the nanotubes.

Effects on Steroid 5-Alpha Reductase Gene Expression of Thai Rice Bran Extracts and Molecular Dynamics Study on SRD5A2

Simple Summary

Dihydrotestosterone (DHT), the most potent androgen hormone, is an important aetiologic factor of androgenetic alopecia (AGA), or hair loss. Steroid 5-alpha reductases (SRD5As) increase DHT production in the scalp hair follicles, resulting in hair thinning and hair loss. Even though synthetic SRD5A inhibitors (finasteride and dutasteride) are effective in treating AGA, they cause adverse effects. This has led to an increased interest in alternative treatments from natural sources. The value of Thai rice bran has increased because several of its components may have use in AGA treatment. This study aimed to compare the suppression of the expression of SRD5A genes (type 1–3) exerted by several Thai rice bran extracts and investigate the interactional mechanism of their components towards SRD5A type 2. Tubtim Chumphae rice bran (TRB) had the highest sum of overall bioactive compounds. Among all extracts, the expression of SRD5A genes was suppressed by TRB as well as finasteride. In silico simulation showed that α-tocopherol had the greatest interaction with SRD5A type 2. Our findings identified α-tocopherol as the key bioactive in TRB; it could be developed as an anti-hair loss product.

Abstract

Steroid 5-alpha reductases (SRD5As) are responsible for the conversion of testosterone to dihydrotestosterone, a potent androgen, which is the aetiologic factor of androgenetic alopecia. This study aimed to compare the SRD5A gene expression suppression activity exerted by Thai rice bran extracts and their components and investigate the interactional mechanism between bioactive compounds and SRD5A2 using molecular dynamics (MD) simulation. Bran of Oryza sativa cv. Tubtim Chumphae (TRB), Yamuechaebia Morchor (YRB), Riceberry (RRB), and Malinil Surin (MRB), all rice milling by-products, was solvent-extracted. The ethanolic extract of TRB had the highest sum of overall bioactive compounds (γ-oryzanol; α-, β-, and γ-tocopherol; phenolics; and flavonoids). Among all extracts, TRB greatly downregulated the expression of SRD5A1, SRD5A2, and SRD5A3; there were no significant differences between TRB and finasteride regarding SRD5A suppression. The linear relationship and principal component analysis supported that the α-tocopherol content was correlated with the SRD5A suppression exerted by TRB. Furthermore, MD simulation demonstrated that α-tocopherol had the highest binding affinity towards SRD5A2 by interacting with residues Phe118 and Trp201. Our findings indicate that α-tocopherol effectively downregulates the expression of SRD5A genes and inhibits SRD5A2 activity, actions that are comparable to standard finasteride. TRB, a source of α-tocopherol, could be developed as an anti-hair loss product.

The structure-based virtual screening of non-benzofuran inhibitors against M. tuberculosis Pks13-TE for anti-tuberculosis phenotypic discovery

Structure-based virtual screening against M. tuberculosis Pks13-TE was performed for anti-tuberculosis phenotypic discovery.

Studying the Binding Modes of Novel 2-Aminopyridine Derivatives as Effective and Selective c-Met Kinase Type 1 Inhibitors Using Molecular Modeling Approaches

The mesenchymal epithelial cell transforming factor c-Met, encoded by c-Met proto-oncogene and known as a high-affinity receptor for Hepatocyte Growth Factor (HGF), is one of the receptor tyrosine kinases (RTKs) members. The HGF/c-Met signaling pathway has close correlation with tumor growth, invasion and metastasis. Thus, c-Met kinase has emerged as a prominent therapeutic target for cancer drug discovery. Recently a series of novel 2-aminopyridine derivatives targeting c-Met kinase with high biological activity were reported. In this study, 3D quantitative structure-activity relationship (QSAR), molecular docking and molecular dynamics simulations (MD) were employed to research the binding modes of these inhibitors.The results show that both the atom-based and docking-based CoMFA (Q² = 0.596, R² = 0.950 in atom-based model and Q² = 0.563, R² = 0.985 in docking-based model) and CoMSIA (Q² = 0.646, R² = 0.931 in atom-based model and Q² = 0.568, R² = 0.983 in docking-based model) models own satisfactory performance with good reliabilities and powerful external predictabilities. Molecular docking study suggests that Tyr1230 and Arg1208 might be the key residues, and electrostatic and hydrogen bond interactions were shown to be vital to the activity, concordance with QSAR analysis. Then MD simulation was performed to further explore the binding mode of the most potent inhibitor. The obtained results provide important references for further rational design of c-Met Kinase type I inhibitors.

In silico design and analysis of NS4B inhibitors against hepatitis C virus

The hepatitis C virus is a communicable disease that gradually harms the liver leading to cirrhosis and hepatocellular carcinoma. Important therapeutic interventions have been reached since the discovery of the disease. However, its resurgence urges the need for new approaches against this malady. The NS4B receptor is one of the important proteins for Hepatitis C Virus RNA replication that acts by mediating different viral properties. In this work, we opt to explore the relationships between the molecular structures of biologically tested NS4B inhibitors and their corresponding inhibitory activities to assist the design of novel and potent NS4B inhibitors. For that, a set of 115 indol-2-ylpyridine-3-sulfonamides (IPSA) compounds with inhibitory activity against NS4B is used. A hybrid genetic algorithm combined with multiple linear regressions (GA-MLR) was implemented to construct a predictive model. This model was further used and applied to a set of compounds that were generated based on a pharmacophore modeling study combined with virtual screening to identify structurally similar lead compounds. Multiple filtrations were implemented for selecting potent hits. The selected hits exhibited advantageous molecular features, allowing for favorable inhibitory activity against HCV. The results showed that 7 out of 1285 screened compounds, were selected as potent candidate hits where Zinc14822482 exhibits the best predicted potency and pharmacophore features. The predictive pharmacokinetic analysis further justified the compounds as potential hit molecules, prompting their recommendation for a confirmatory biological evaluation. We believe that our strategy could help in the design and screening of potential inhibitors in drug discovery.Communicated by Ramaswamy H. Sarma.

Identification of Potential COX-2 Inhibitors for the Treatment of Inflammatory Diseases Using Molecular Modeling Approaches

Non-steroidal anti-inflammatory drugs are inhibitors of cyclooxygenase-2 (COX-2) that were developed in order to avoid the side effects of non-selective inhibitors of COX-1. Thus, the present study aims to identify new selective chemical entities for the COX-2 enzyme via molecular modeling approaches. The best pharmacophore model was used to identify compounds within the ZINC database. The molecular properties were determined and selected with Pearson’s correlation for the construction of quantitative structure–activity relationship (QSAR) models to predict the biological activities of the compounds obtained with virtual screening. The pharmacokinetic/toxicological profiles of the compounds were determined, as well as the binding modes through molecular docking compared to commercial compounds (rofecoxib and celecoxib). The QSAR analysis showed a fit with R = 0.9617, R² = 0.9250, standard error of estimate (SEE) = 0.2238, and F = 46.2739, with the tetra-parametric regression model. After the analysis, only three promising inhibitors were selected, Z-964, Z-627, and Z-814, with their predicted pIC₅₀ (−log IC₅₀) values, Z-814 = 7.9484, Z-627 = 9.3458, and Z-964 = 9.5272. All candidates inhibitors complied with Lipinski’s rule of five, which predicts a good oral availability and can be used in in vitro and in vivo tests in the zebrafish model in order to confirm the obtained in silico data.

Identification of New Rofecoxib-Based Cyclooxygenase-2 Inhibitors: A Bioinformatics Approach

The cyclooxygenase-2 receptor is a therapeutic target for planning potential drugs with anti-inflammatory activity. The selective cyclooxygenase-2 (COX-2) inhibitor rofecoxib was selected as a pivot molecule to perform virtual ligand-based screening from six commercial databases. We performed the search for similarly shaped Rapid Overlay of Chemical Structures (ROCS) and electrostatic (EON) compounds. After, we used pharmacokinetic and toxicological parameters to determine the best potential compounds, obtained through the softwares QikProp and Derek, respectively. Then, the compounds proceeded to the molecular anchorage study, which showed promising results of binding affinity with the hCOX-2 receptor: LMQC72 (∆G = -11.0 kcal/mol), LMQC36 (∆G = -10.6 kcal/mol), and LMQC50 (∆G = -10.2 kcal/mol). LMQC72 and LMQC36 showed higher binding affinity compared to rofecoxib (∆G = -10.4 kcal/mol). Finally, molecular dynamics (MD) simulations were used to evaluate the interaction of the compounds with the target hCOX-2 during 150 ns. In all MD simulation trajectories, the ligands remained interacting with the protein until the end of the simulation. The compounds were also complexing with hCOX-2 favorably. The compounds obtained the following affinity energy values: rofecoxib: ΔGbind = -45.31 kcal/mol; LMQC72: ΔGbind = -38.58 kcal/mol; LMQC36: ΔGbind = -36.10 kcal/mol; and LMQC50: ΔGbind = -39.40 kcal/mol. The selected LMQC72, LMQC50, and LMQC36 structures showed satisfactory pharmacokinetic results related to absorption and distribution. The toxicological predictions of these compounds did not display alerts for possible toxic groups and lower risk of cardiotoxicity compared to rofecoxib. Therefore, future in vitro and in vivo studies are needed to confirm the anti-inflammatory potential of the compounds selected here with bioinformatics approaches based on rofecoxib ligand.

Chemical Composition, Antimicrobial Properties of Siparuna guianensis Essential Oil and a Molecular Docking and Dynamics Molecular Study of its Major Chemical Constituent

The essential oil of Siparuna guianensis was obtained by hydrodistillation. The identification of the chemical compounds was performed by gas chromatography coupled with mass spectrometry (GC/MS). Antimicrobial activity was investigated for four microorganisms: Streptococcus mutans (ATCC 3440), Enterococcus faecalis (ATCC 4083), Escherichia coli (ATCC 25922), and Candida albicans (ATCC-10231). The studies of doping and molecular dynamics were performed with the molecule that presented the highest concentration of drug–target proteins, 1IYL (C. albicans), 1C14 (E. coli), 2WE5 (E. faecalis), and 4TQX (S. mutans). The main compounds identified were: Curzerene (7.1%), γ-Elemene (7.04%), Germacrene D (7.61%), trans-β-Elemenone (11.78%), and Atractylone (18.65%). Gram positive bacteria and fungi were the most susceptible to the effects of the essential oil. The results obtained in the simulation showed that the major compound atractylone interacts with the catalytic sites of the target proteins, forming energetically favourable systems and remaining stable during the period of molecular dynamics.

Forecasting structure of natural products through color formation process by thin layer chromatography

With booming of computer technology, it is feasible to quantitatively extract valuable information from readily available image of objects, which dramatically reduces the cost and improves the efficiency. In this work, a structural classification method, based on data extracted from color formation process on thin layer chromatography (TLC) plates through computer processing, was established for natural products. Representative natural products exhibited good clustering and separation according to the extracted color feature, and structure of natural products can be classified by the distribution region in the color system. This method provides structural information for typical types of natural products directly from the formed color on TLC, which is very efficient and make portable device-based structure analysis of natural products possible. In addition, a general mechanism of color formation was proposed. This method is free from special instrument, high-throughput, and would facilitate large-scale screening of bioactives from natural sources.

Identification of Phosphoinositide-3 Kinases Delta and Gamma Dual Inhibitors Based on the p110δ/γ Crystal Structure

Background:

Phosphoinositide-3 kinases (PI3Ks) are key signaling molecules that affect a diverse array of biological processes in cells, including proliferation, differentiation, survival, and metabolism. The abnormal activity of PI3K signals is closely related to the occurrence of many diseases, which has become a very promising drug target, especially for the treatment of cancer. PI3Kδ/γ inhibitors can reduce toxicity concerns for chronic indications such as asthma and rheumatoid arthritis compared with pan PI3Ks inhibitors.

Methods:

With the aim of finding more effective PI3Kδ/γ dual inhibitors, virtual screening, ADMET prediction Molecular Dynamics (MD) simulations and MM-GBSA were executed based on the known p110δ/γ crystal structure. Compound ZINC28564067 with high docking score and low toxicity was obtained.

Results:

By MD simulations and MM-GBSA, we could observe that ZINC28564067 had more favorable conformation binding to the PI3Kδ/γ than the original ligands.

Conclusion:

The results provided a rapid approach for the discovery of novel PI3Kδ/γ dual inhibitors which might be a potential anti-tumor lead compound.

Molecular modeling approaches of selective adenosine receptor type 2A agonists as potential anti-inflammatory drugs

Adenosine A_2A receptor (A_2AR) is the predominant receptor in immune cells, where its activation triggers cAMP-mediated immunosuppressive signaling and the underlying inhibition of T cells activation and T cells-induced effects mediated by cAMP-dependent kinase proteins mechanisms. In this study, were used ADME/Tox, molecular docking and molecular dynamics simulations to investigate selective adenosine A_2AR agonists as potential anti-inflammatory drugs. As a result, we obtained two promising compounds (A and B) that have satisfactory pharmacokinetic and toxicological properties and were able to interact with important residues of the A_2AR binding cavity and during the molecular dynamics simulations were able to keep the enzyme complexed.Communicated by Ramaswamy H. Sarma.

Design and synthesis of new drugs inhibitors of Candida albicans hyphae and biofilm formation by upregulating the expression of TUP1 transcription repressor gene

Candida albicans is a common human fungal pathogen that causes disease ranging from superficial to lethal infections. C. albicans grows as budding yeast which can transform into hyphae in response to various environmental or biological stimuli. Although both forms have been associated with virulence, the hyphae form is responsible for the formation of multi-drug resistance biofilm. Here, new compounds were designed to selectively inhibit C. albicans hyphae formation without affecting human cells to afford sufficient safety. The newly designed 5-[3-substitued-4-(4-substituedbenzyloxy)-benzylidene]-2-thioxo-thiazolidin-4-one derivatives, named SR, showed very specific and effective inhibition activity against C. albicans hyphae formation. SR compounds caused hyphae inhibition activity at concentrations 10-40 fold lower than the concentration required to inhibit Candida yeast and bacterial growths. The anti-hyphae inhibition activities of SR compounds were via activation of the hyphae transcription repressor gene, TUP1. Correlation studies between the expression of TUP1 gene and the activity of SR compounds confirmed that the anti-C. albicans activities of SR compounds were via inhibition of hyphae formation. The newly designed SR compounds showed 10-40% haemolytic activity on human erythrocytes when compared to 100% haemolysis by 0.1% triton employed as positive control. Furthermore, theoretical prediction of absorption, distribution, metabolism, excretion, and toxicity (ADMET) of SR compounds confirmed their safety, efficient metabolism and possible oral bioavailability. With the minimal toxicity and significant activity of the newly-designed SR compounds, a future optimization of pharmaceutical formulation may develop a promising inhibitor of hyphal formation not only for C. albicans but also for other TUP1- dependent dimorphic fungal infections.

Identification of Novel Chemical Entities for Adenosine Receptor Type 2A Using Molecular Modeling Approaches

Adenosine Receptor Type 2A (A_2AAR) plays a role in important processes, such as anti-inflammatory ones. In this way, the present work aimed to search for compounds by pharmacophore-based virtual screening. The pharmacokinetic/toxicological profiles of the compounds, as well as a robust QSAR, predicted the binding modes via molecular docking. Finally, we used molecular dynamics to investigate the stability of interactions from ligand-A_2AAR. For the search for A_2AAR agonists, the UK-432097 and a set of 20 compounds available in the BindingDB database were studied. These compounds were used to generate pharmacophore models. Molecular properties were used for construction of the QSAR model by multiple linear regression for the prediction of biological activity. The best pharmacophore model was used by searching for commercial compounds in databases and the resulting compounds from the pharmacophore-based virtual screening were applied to the QSAR. Two compounds had promising activity due to their satisfactory pharmacokinetic/toxicological profiles and predictions via QSAR (Diverset 10002403 pEC₅₀ = 7.54407; ZINC04257548 pEC₅₀ = 7.38310). Moreover, they had satisfactory docking and molecular dynamics results compared to those obtained for Regadenoson (Lexiscan^®), used as the positive control. These compounds can be used in biological assays (in vitro and in vivo) in order to confirm the potential activity agonist to A_2AAR.

In Silico Strategies in Tuberculosis Drug Discovery

Tuberculosis (TB) remains a serious threat to global public health, responsible for an estimated 1.5 million mortalities in 2018. While there are available therapeutics for this infection, slow-acting drugs, poor patient compliance, drug toxicity, and drug resistance require the discovery of novel TB drugs. Discovering new and more potent antibiotics that target novel TB protein targets is an attractive strategy towards controlling the global TB epidemic. In silico strategies can be applied at multiple stages of the drug discovery paradigm to expedite the identification of novel anti-TB therapeutics. In this paper, we discuss the current TB treatment, emergence of drug resistance, and the effective application of computational tools to the different stages of TB drug discovery when combined with traditional biochemical methods. We will also highlight the strengths and points of improvement in in silico TB drug discovery research, as well as possible future perspectives in this field.

Insight into the Interaction Mechanism of Nicotine, NNK, and NNN with Cytochrome P450 2A13 Based on Molecular Dynamics Simulation

Tobacco smoke contains various cancer-causing toxic substances, including nicotine and nitrosamines 4-(methylnitrosamino)-1-(3-pyridyl)-1-butanone (NNK) and N'-nitrosonornicotine (NNN). The cytochrome 2A13 is involved in nicotine metabolism and in the activation of the pro-carcinogenic agents NNK and NNN, by means of α-hydroxylation reactions. Despite the significance of cytochrome 2A13 in the biotransformation of these molecules, its conformational mechanism and the molecular basis involved in the process are not fully understood. In this study, we used molecular dynamics and principal component analysis simulations for an in-depth analysis of the essential protein motions involved in the interaction of cytochrome 2A13 with its substrates. We also evaluated the interaction of these substrates with the amino acid residues in the binding pocket of cytochrome 2A13. Furthermore, we quantified the nature of these chemical interactions from free energy calculations using the Molecular Mechanics/Generalized Born Surface Area method. The ligands remained favorably oriented toward compound I (cytochrome P450 O═Fe^IV state), to undergo α-hydroxylation. The hydrogen bond with asparagine 297 was essential to maintaining the substrates in a favorable catalytic orientation. The plot of first principal motion vs second principal motion revealed that the enzyme's interaction with nicotine and NNK involved different conformational subgroups, whereas the conformational subgroups in the interaction with NNN are more similar. These results provide new mechanistic insights into the mode of interaction of the substrates with the active site of cytochrome 2A13, in the presence of compound I, which is essential for α-hydroxylation.

Role of N-terminus in function and dynamics of sirtuin 7: an in silico study

The sirtuin family comprises seven NAD⁺-dependent histone deacetylases named SIRT1 to SIRT7. The least investigated SIRT7 is currently considered as a promising therapeutic target for cardiovascular diseases, diabetes and different types of cancer. So far, its structure was not experimentally resolved, except of a fragment of its N-terminus. The aim of this study was to create in silico model of SIRT7 containing its core together with N-terminus, which is known to affect the enzyme's catalytic activity and to find pockets that could be targeted by structure-based virtual screening. Homology model of SIRT7 was prepared using X-ray structures of other sirtuins and a resolved fragment of the N-terminus of SIRT7 as templates. All atom-unbiased molecular dynamics simulations were performed. It was found that N-terminus of SIRT7 remains in spatial proximity of the catalytic core for considerable fraction of time, and therefore, it may affect its catalytic activity by helping the enzyme to hold the substrate peptide. It may also participate in holding and release of the cofactor. Preferred orientations of NAD⁺ and acetyl-lysine inside SIRT7 were found, with all components forming a stable complex. Molecular dynamics provided an ensemble of conformations that will be targeted with virtual screening. Reliable in silico structure of SIRT7 will be a useful tool in searching for its inhibitors, which can be potential drugs in cancer treatment.Communicated by Ramaswamy H. Sarma.

Discovery of potential sclerostin inhibitors from plants with loop2 region of sclerostin inhibition by interacting with residues outside Pro-Asn-Ala-Ile-Gly motif

Sclerostin, an antagonist of the Wnt/β-catenin signaling pathway, was discovered as a potential therapeutic target for stimulating bone formation in osteoporosis. In this study, molecular docking was employed to predict the binding of 29 herbal compounds, which were reported as bone formation stimulators, to the loop2 region of sclerostin. Then, the 50 ns molecular dynamics (MD) simulation of the complexes between sclerostin and the top 10 hits obtained from molecular docking were carried out. Root mean square deviations (RMSDs) analysis of MD trajectories pointed out that all ligands-complexes remain stable throughout the duration of MD simulations. In addition, the molecular mechanics/generalized born surface area (MM/GBSA) binding free energy and energy decomposition analyses were determined. The results here suggested that baicalin is the most promising inhibitor of sclerostin. Interestingly, baicalin binds to sclerostin via the hydrophobic interaction with the amino acid residues on loop2 region but outside the Pro-Asn-Ala-Ile-Gly (PNAIG) motif, particularly the Arg-Gly-Lys-Trp-Trp-Arg (RGKWWR) motif. This finding could be a novel strategy for developing new sclerostin inhibitors in the future.Communicated by Ramaswamy H. Sarma.

In Silico Study to Identify New Antituberculosis Molecules from Natural Sources by Hierarchical Virtual Screening and Molecular Dynamics Simulations

Tuberculosis (TB) is an infection caused by Mycobacterium tuberculosis, responsible for 1.5 million documented deaths in 2016. The increase in reported cases of M. tuberculosis resistance to the main drugs show the need for the development of new and efficient drugs for better TB control. Based on these facts, this work aimed to use combined in silico techniques for the discovery of potential inhibitors to β-ketoacyl-ACP synthase (MtKasA). Initially compounds from natural sources present in the ZINC database were selected, then filters were sequentially applied by virtual screening, initially with pharmacophoric modeling, and later the selected compounds (based on QFIT scores) were submitted to the DOCK 6.5 program. After recategorization of the variables (QFIT score and GRID score), compounds ZINC35465970 and ZINC31170017 were selected. These compounds showed great hydrophobic contributions and for each established system 100 ns of molecular dynamics simulations were performed and the binding free energy was calculated. ZINC35465970 demonstrated a greater capacity for the KasA enzyme inhibition, with a ΔG_bind = -30.90 kcal/mol and ZINC31170017 presented a ΔG_bind = -27.49 kcal/mol. These data can be used in other studies that aim at the inhibition of the same biological targets through drugs with a dual action.

Chemical profile of Lippia thymoides, evaluation of the acetylcholinesterase inhibitory activity of its essential oil, and molecular docking and molecular dynamics simulations

The essential oils of the fresh and dry flowers, leaves, branches, and roots of Lippia thymoides were obtained by hydrodistillation and analyzed using gas chromatography (GC) and GC-mass spectrometry (MS). The acetylcholinesterase inhibitory activity of the essential oil of fresh leaves was investigated on silica gel plates. The interactions of the key compounds with acetylcholinesterase were simulated by molecular docking and molecular dynamics studies. In total, 75 compounds were identified, and oxygenated monoterpenes were the dominant components of all the plant parts, ranging from 19.48% to 84.99%. In the roots, the main compounds were saturated and unsaturated fatty acids, having contents varying from 39.5% to 32.17%, respectively. In the evaluation of the anticholinesterase activity, the essential oils (detection limit (DL) = 0.1 ng/spot) were found to be about ten times less active than that of physostigmine (DL = 0.01ng/spot), whereas thymol and thymol acetate presented DL values each of 0.01 ng/spot, equivalent to that of the positive control. Based on the docking and molecular dynamics studies, thymol and thymol acetate interact with the catalytic residues Ser203 and His447 of the active site of acetylcholinesterase. The binding free energies (ΔGbind) for these ligands were -18.49 and -26.88 kcal/mol, demonstrating that the ligands are able to interact with the protein and inhibit their catalytic activity.

An insight into paracetamol and its metabolites using molecular docking and molecular dynamics simulation

Paracetamol is a relatively safe analgesia/antipyretic drug without the risks of addiction, dependence, tolerance, and withdrawal when used alone. However, when administrated in an opioid/paracetamol combination product, which often contains a large quantity of paracetamol, it can be potentially dangerous due to the risk of hepatotoxicity. Paracetamol is known to be metabolized into N-(4-hydroxyphenyl)-arachidonamide (AM404) via fatty acid amide hydrolase (FAAH) and into N-acetyl-p-benzoquinone imine (NAPQI) via cytochrome P450 (CYP) enzymes. However, the underlying mechanism of paracetamol is still unclear. In addition, paracetamol has the potential to interact with other drugs that are also involved with CYP family enzymes (inducer/inhibitor/substrate), an example being illicit drugs. In our present work, we looked into the relationship between paracetamol and its metabolites (AM404 and NAPQI) using molecular docking and molecular dynamics (MD) simulations. We first carried out a series of molecular docking studies between paracetamol/AM404/NAQPI and their reported targets, including CYP 2E1, FAAH, TRPA1, CB1, and TRPV1. Subsequently, we performed MD simulations and energy decomposition for CB1-AM404, TRPV1-AM404, and TRPV1-NAPQI for further investigation of the dynamics interactions. Finally, we summarized and discussed the reported drug-drug interactions between paracetamol and central nervous system drugs, especially illicit drugs. Overall, we are able to provide new insights into the structural and functional roles of paracetamol and its metabolites that can inform the potential prevention and treatment of paracetamol overdose. Graphical abstract Paracetamol and its metabolites.