3D QSAR pharmacophore modeling, in silico screening, and density functional theory (DFT) approaches for identification of human chymase inhibitors

Unveiling the intricacies of allosteric regulation in aspartate kinase from the Wolbachia endosymbiont of Brugia Malayi: Mechanistic and therapeutic insights

Aspartate kinase (AK), an enzyme from the Wolbachia endosymbiont of Brugia malayi (WBm), plays a pivotal role in the bacterial cell wall and amino acid biosynthesis, rendering it an attractive candidate for therapeutic intervention. Allosteric inhibition of aspartate kinase is a prevalent mode of regulation across microorganisms and plants, often modulated by end products such as lysine, threonine, methionine, or meso-diaminopimelate. The intricate and diverse nature of microbial allosteric regulation underscores the need for rigorous investigation. This study employs a combined experimental and computational approach to decipher the allosteric regulation of WBmAK. Molecular Dynamics (MD) simulations elucidate that ATP (cofactor) and ASP (substrate) binding induce a closed conformation, promoting enzymatic activity. In contrast, the binding of lysine (allosteric inhibitor) leads to enzyme inactivation and an open conformation. The enzymatic assay demonstrates the optimal activity of WBmAK at 28 °C and a pH of 8.0. Notably, the allosteric inhibition study highlights lysine as a more potent inhibitor compared to threonine. Importantly, this investigation sheds light on the allosteric mechanism governing WBmAK and imparts novel insights into structure-based drug discovery, paving the way for the development of effective inhibitors against filarial pathogens.

Lead generation of UPPS inhibitors targeting MRSA: Using 3D-QSAR pharmacophore modeling, virtual screening, molecular docking, and molecular dynamic simulations

Undecaprenyl Pyrophosphate Synthase (UPPS) is a vital target enzyme in the early stages of bacterial cell wall biosynthesis. UPPS inhibitors have antibacterial activity against resistant strains such as MRSA and VRE. In this study, we used several consecutive computer-based protocols to identify novel UPPS inhibitors. The 3D QSAR pharmacophore model generation (HypoGen algorithm) protocol was used to generate a valid predictive pharmacophore model using a set of UPPS inhibitors with known reported activity. The developed model consists of four pharmacophoric features: one hydrogen bond acceptor, two hydrophobic, and one aromatic ring. It had a correlation coefficient of 0.86 and a null cost difference of 191.39, reflecting its high predictive power. Hypo1 was proven to be statistically significant using Fischer's randomization at a 95% confidence level. The validated pharmacophore model was used for the virtual screening of several databases. The resulting hits were filtered using SMART and Lipinski filters. The hits were docked into the binding site of the UPPS protein, affording 70 hits with higher docking affinities than the reference compound (6TC, - 21.17 kcal/mol). The top five hits were selected through extensive docking analysis and visual inspection based on docking affinities, fit values, and key residue interactions with the UPPS receptor. Moreover, molecular dynamic simulations of the top hits were performed to confirm the stability of the protein-ligand complexes, yielding five promising novel UPPS inhibitors.

The identification of novel inhibitors of human angiotensin-converting enzyme 2 and main protease of Sars-Cov-2: A combination of in silico methods for treatment of COVID-19

The angiotensin-converting enzyme 2 (ACE2) and main protease (MPro), are the putative drug candidates for the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). In this study, we performed 3D-QSAR pharmacophore modeling and screened 1,264,479 ligands gathered from Pubchem and Zinc databases. Following the calculation of the ADMET properties, molecular docking was carried out. Moreover, the de novo ligand design was performed. MD simulation was then applied to survey the behavior of the ligand-protein complexes. Furthermore, MMPBSA has utilized to re-estimate the binding affinities. Then, a free energy landscape was used to find the most stable conformation of the complexes. Finally, the hybrid QM-MM method was carried out for the precise calculation of the energies.

The Hypo1 pharmacophore model was selected as the best model. Our docking results indicate that the compounds ZINC12562757 and 112,260,215 were the best potential inhibitors of the ACE2 and MPro, respectively. Furthermore, the Evo_1 compound enjoys the highest docking energy among the designed de novo ligands. Results of RMSD, RMSF, H-bond, and DSSP analyses have demonstrated that the lead compounds preserve the stability of the complexes’ conformation during the MD simulation. MMPBSA data confirmed the molecular docking results. The results of QM-MM showed that Evo_1 has a stronger potential for specific inhibition of MPro, as compared to the 112,260,215 compound.

Network pharmacology based high throughput screening for identification of multi targeted anti-diabetic compound from traditionally used plants

The incurable Type 2 diabetes mellitus (T2DM) has now been considered a pandemic with only supportive care in existence. Due to the adverse effects of available anti-diabetic drugs, there arises a great urgency to develop new drug molecules. One of the alternatives that can be considered for the treatment of T2DM are natural compounds from traditionally used herbal medicine. The present study undertakes, an integrated multidisciplinary concept of Network Pharmacology to evaluate the efficacy of potent anti-diabetic compound from traditionally used anti-diabetic plants of north east India and followed by DFT analysis. In the course of the study, 22 plant species were selected on the basis of their use in traditional medicine for the treatment of T2DM by various ethnic groups of the north eastern region of India. Initially, a library of 1053 compounds derived from these plants was generated. This was followed by network preparation between compounds and targets based on the docking result. The compounds having the best network property were considered for DFT analysis. We have identified that auraptene, a monoterpene coumarin for its activity in the management of Type 2 diabetes mellitus and deciphered its unexplored probable mechanisms. Molecular dynamics simulation of the ligand-protein complexes also reveals the stable binding of auraptene with the target proteins namely, Protein Kinase C θ, Glucocorticoid receptor, 11-β hydroxysteroid dehydrogenase 1 and Aldose Reductase, all of which form uniform interactions throughout the MD simulation trajectory. Therefore, this finding could provide new insights for the development of a new anti-diabetic drug.Communicated by Ramaswamy H. Sarma.

A novel pharmacophore model on PAEs' estrogen and thyroid hormone activities using the TOPSIS and its application in molecule modification

In the proposed model, the estrogen activity values and thyroid hormone activity values of PAEs molecules were normalized using the TOPSIS method by eliminating the dimension coefficients, and the comprehensive activity values of estrogen and thyroid hormone were obtained by analyzing the activity of each hormone and assigning the corresponding weight. The five pharmacophore models of hormone combined activity were constructed using the comprehensive activity values. Hypol 1 was the optimal pharmacophore model, showing good predictive power and significance. Then, the DBP, DNOP, and DMP molecules in environmental priority control pollutants were selected as the target molecules to perform common substitution reactions of hydrogen bond donor. Eleven PAEs derivative molecules with significantly reduced combined activity and single activity were screened. In analysis of the differences before and after modification of the docking parameters and amino acid residues before and after modification of PAEs and their derivatives, the reduced closeness between ligand and receptor leads to the decrease of thyroid hormones and estrogen activities. Moreover, the establishment of the models, not only shows that the PAEs hormone activity has certain linear relationships with the physical parameters of molecules but also shows that thyroid hormone activity and estrogen activity of PAEs is consistent with the hormone combined activity. The results confirmed the feasibility of the modified PAEs modification scheme with reduced combined activities of hormones, providing an important theoretical method for the construction of the pharmacophore model of combined activities of hormones and the study of PAEs derivative molecules.

Theoretical Design of Biodegradable Phthalic Acid Ester Derivatives in Marine and Freshwater Environments

The biodegradability of phtalic acid esters in marine and freshwater environments was characterized by their binding free energy with corresponding degrading enzymes. According to comprehensive biodegradation effects weights, the binding free energy values were converted into dimensionless efficacy coefficient using ratio normalization method. Then, considering comprehensive dual biodegradation effects value and the structural parameters of PAEs in both marine and freshwater environments, a 3D‐QSAR pharmacophore model was constructed, five PAE derivatives (DBP−COOH, DBP−CHO, DBP−OH, DINP−NH₂, and DINP−NO₂) were screened out based on their environmental friendliness, functionality and stability. The prediction of biodegradation effects on five PAE derivatives by biodegradation models in marine and freshwater environment increased by 15.90 %, 15.84 %, 27.21 %, 12.33 %, and 8.32 %, and 21.57 %, 15.21 %, 20.99 %, 15.10 %, and 9.74 %, respectively. By simulating the photodegradation path of the PAE derivative molecular, it was found that DBP−OH can generate ^.OH and provides free radicals for the photodegradation of microplastics in the environment.

In-silico strategies for identification of potent inhibitor for MMP-1 to prevent metastasis of breast cancer

Matrix Metalloproteinase-1 (MMP-1) has been often upregulated in advanced breast cancers, known to participate in ECM degradation, migration, invasion, thus leading to metastasis. Due to these effects, the condition is often reported to inversely correlate with survival in advanced breast cancers. In the present study, in-silico method was adopted based on selective non zinc binding inhibitors of MMP-1. ADME properties were predicted for PASS filtered compounds and docking calculations were performed using Glide XP and IFD protocols of Schrodinger program. We identified six ligands as potent inhibitors and validated by observing structures and the interactions of MMP-1. The identified hits were validated using molecular dynamics simulation studies. Electronic structure analysis was performed for two top hit compounds myricetin and quercetin using density function theory (DFT) at B3LYP/6-31**G level to understand their molecular reactivity. Finally, one compound myricetin has emerged as the structurally stable compound with -7.801 kcal/mol and reasonable pose inside the binding site. Molecular dynamics results indicated that myricetin forms a stable interaction with the key amino acid residues such as Glu209, Glu219, Tyr240 and Pro238. In addition, it did not form any binding with the catalytic zinc at its active site. The interaction pattern of myricetin at its substrate binding site exhibited to be potent MMP-1 inhibitor. DFT study also showed that it has more potent inhibitory effect and solubility. These factors altogether show that myricetin could be considered as the best among the compounds evaluated in inhibiting MMP-1 thereby preventing metastasis of breast cancer. Communicated by Ramaswamy H. Sarma.

Efficacy coefficient method assisted quadruple-activities 3D-QSAR pharmacophore model for application in environmentally friendly PAE molecular modification

Phthalate acid esters (PAEs) are among the most widely used plasticizers in plastic products. They are easily diffused from plastic during use and seriously affect the environment and human health. Therefore, designing environmentally friendly PAE derivatives has important practical applications. In this paper, the environmentally friendly molecular modification of PAEs was carried out according to a comprehensive structural evaluation based on a three-dimensional quantitative structure-activity relationship (3D-QSAR) pharmacophore model of four activity modes. First, the efficacy coefficient method was used to process the mobility, toxicity, degradation and bioconcentration data of the PAEs to calculate comprehensive evaluation values. The PAE 3D-QSAR pharmacophore complex model was constructed based on the PAE four-activity comprehensive evaluation value (a comprehensive value representing the mobility, toxicity, degradation and bioconcentration of the PAEs), and a total of 4 PAE derivatives with reduced comprehensive evaluation values were obtained. Functional evaluation of the derivatives showed that the five PAEs with lower comprehensive evaluation values were stable in the environment, while the insulating properties of the derivative molecules were less affected. Following the four-activity pharmacophore model (Hypo 1) of the target molecules, dimethyl phthalate (DMP) and di-n-octyl phthalate (DNOP), comprehensive evaluation models and their mobility, toxicity, degradation and bioconcentration single-activity models, the substitution sites selected by the comprehensive evaluation model were demonstrated to be highly representative. By constructing a two-dimensional quantitative structure-activity relationship (2D-QSAR) model of the comprehensive evaluation values of the PAEs and the four single-effect 2D-QSAR models of their derivatives, the different effects of the five key parameters on the comprehensive evaluation values, toxicity, degradation, mobility and bioconcentration of molecules were analysed.

Detection Method of Environmentally Friendly Non-POP PBDEs by Derivatization-Enhanced Raman Spectroscopy Using the Pharmacophore Model

Background:

Polybrominated diphenyl ethers (PBDEs) are dangerous for the environment and human health because of their persistent organic pollutant (POP) characteristics, which have attracted extensive research attention. Raman spectroscopy is a simple highly sensitive detection operation. This study was performed to obtain environmentally friendly non-POP PBDE derivatives with simple detection-based molecular design and provide theoretical support for establishing enhanced Raman spectroscopic detection techniques.

Methods:

A three-dimensional quantitative structure-activity relationship (3DQSAR) pharmacophore model of characteristic PBDE Raman spectral was established using 20 and 10 PBDEs as training and test sets, respectively. Full-factor experimental design was used to modify representative commercial PBDEs, and their flame retardancy and POP characteristics were evaluated.

Results:

The pharmacophore model (Hypo1) exhibited good predictive ability with the largest correlation coefficient (R2) of 0.88, the smallest root mean square (RMS) value of 0.231, and total cost of 81.488 with a configuration value of 12.56 (˂17).74 monosubstituted and disubstituted PBDE derivatives were obtained based on the Hypo 1 pharmacophore model and full-factor experimental design auxiliary. Twenty PBDE derivatives were screened, and their flame-retardant capabilities were enhanced and their migration and bio-concentration were reduced (log(KOW) <5), with unchanged toxicity and high biodegradability. The Raman spectral intensities increased up to 380%. In addition, interference analysis of the Raman peaks by group frequency indicated that the 20 PBDE derivatives were easily detected with no interference in gaseous environments.

Conclusion:

Nine pharmacophore models were constructed in this study; Hypo 1 was the most accurate. Twenty PBDE derivatives showed Raman spectral intensities increased up to 380%; these were classified as new non-POP environmentally friendly flame retardants with low toxicity, low migration, good biodegradability, and low bio-concentrations. 2D QSAR analysis showed that the most positive Milliken charge and lowest occupied orbital energy were the main contributors to the PBDE Raman spectral intensities. Raman peak analysis revealed no interference between the derivatives in gaseous environments.

Identification of Pak1 inhibitors using water thermodynamic analysis

p21-activated kinases (Paks) play an integral component in various cellular diverse processes. The full activation of Pak is dependent upon several serine residues present in the N-terminal region, a threonine present at the activation loop, and finally the phosphorylation of these residues ensure the complete activation of Pak1. The present study deals with the identification of novel potent candidates of Pak1 using computational methods as anti-cancer compounds. A diverse energy based pharmacophore (e-pharmacophore) was developed using four co-crystal inhibitors of Pak1 having pharmacophore features of 5 (DRDRR), 6 (DRHADR), and 7 (RRARDRP and DRRDADH) hypotheses. These models were used for rigorous screening against e-molecule database. The obtained hits were filtered using ADME/T and molecular docking to identify the high affinity binders. These hits were subjected to hierarchical clustering using dendritic fingerprint inorder to identify structurally diverse molecules. The diverse hits were scored against generated water maps to obtain WM/MM ΔG binding energy. Furthermore, molecular dynamics simulation and density functional theory calculations were performed on the final hits to understand the stability of the complexes. Five structurally diverse novel Pak1 inhibitors (4835785, 32198676, 32407813, 76038049, and 32945545) were obtained from virtual screening, water thermodynamics and WM/MM ΔG binding energy. All hits revealed similar mode of binding pattern with the hinge region residues replacing the unstable water molecules in the binding site. The obtained novel hits could be used as a platform to design potent drugs that could be experimentally tested against cancer patients having increased Pak1 expression.

Designing modified polybrominated diphenyl ether BDE-47, BDE-99, BDE-100, BDE-183, and BDE-209 molecules with decreased estrogenic activities using 3D-QSAR, pharmacophore models coupled with resolution V of the 210-3 fractional factorial design and molecular docking

A 3D-QSAR model was constructed to predict polybrominated diphenyl ether (PBDE) estrogenic activities expressed as median effective concentrations (pEC₅₀), and resolution V of the 2^10-3 fractional factorial design and a pharmacophore model were used to modify the target PBDE molecules BDE-47, BDE-99, BDE-100, BDE-183, and BDE-209 to decrease the estrogenic activities. The persistent-organic-pollutant-related and flame-retardant properties of the modified molecules were evaluated. The mechanisms involved in decreasing PBDE estrogenic activities were explored through molecular docking. The 3D-QSAR model gave a cross-validated correlation coefficient (q²) of 0.682 (i.e., >0.5) and a non-cross-validated correlation coefficient (r²) of 0.980 (i.e., >0.9). Mono- and di-substitutions and hydrophobic substituent groups gave 40 modified molecules with decreased estrogenic activities, including modified BDE-47 and BDE-99 with pEC₅₀ decreased by >10% and modified BDE-100, BDE-183, and BDE-209 with pEC₅₀ decreased by >20%. The modified molecules had similar flame-retardancy to the unmodified molecules, and lower biotoxicities (by a maximum of 17.27%), persistences (by a maximum of 55.68%), bioconcentration (by 4.28%-23.91%), and long-range transport potentials (by 0.72%-18.47%). Docking indicated that hydrophobic interactions were the main factors affecting PBDE estrogenic activities. The results provide a theoretical basis for designing less estrogenic flame retardants than are currently available.

Identification of novel inhibitor against endonuclease subunit of Influenza pH1N1 polymerase: A combined molecular docking, molecular dynamics, MMPBSA, QMMM and ADME studies to combat influenza A viruses

The influenza H1N1 virus is the causative agent of the flu pandemic in the world. Due to the shortage of effective means of control, it is remained the serious threats to public and avian health. To battle the surge of viral outbreaks, new treatments are crucially needed. The viral RNA polymerase, which is responsible for transcription and replication of the RNA genome, is comprised of subunits PA, PB1 and PB2. PA has endonuclease activity and is a well known target for inhibitor and drug design. In the current study, we employed molecular docking, molecular dynamics (MD), MMPBSA, QMMM and ADME studies to find and propose an inhibitor among 11,873 structures against PA. Our molecular docking, MD, MMPBSA and QMMM studies showed that ZINC15340668 has ideal characteristics as a potent PA inhibitor, and can be used in experimental phase and further development. Also, ADME prediction demonstrated that all physico-chemical parameters are within the acceptable range defined for human use. Molecular mechanism based study revealed that upon inhibitor binding; the flexibility of PA backbone is increased. This observation demonstrates the plasticity of PA active site, and it should be noticed in drug design against PA Influenza A viruses. In the final phase of the study, the efficiency of our proposed hit was tested computationally against mutant drug resistant I38T_PA. Our results exhibited that the hit inhibits the I38T_PA in different manner with high potency.

Novel mutant of Escherichia coli asparaginase II to reduction of the glutaminase activity in treatment of acute lymphocytic leukemia by molecular dynamics simulations and QM-MM studies

L-Asparaginases (ASNase) belong to a family of amidohydrolases, have both asparaginase and glutaminase activity. Acute lymphocytic leukemia (ALL) is an outrageous disease worldwide. Bacterial ASNase has been used for the treatment of ALL. Glutaminase activity of enzyme causes some side effect and it is not essential for anticancer activity. The aim of this study was engineering of Escherichia coli asparaginase II to find a mutant with reduced glutaminase activity by molecular docking, molecular dynamics (MD) and QM-MM (Quantum mechanics molecular dynamics) simulations. Residues with low free energy of binding to Asn and high free binding energy to Gln were chosen for mutagenesis. Then, a mutant with higher glutaminase free binding energy was selected for further studies. Additionally, the MD simulation and QM-MM computation of wild type (WT) were employed and the selected mutated ASNase were analyzed and discussed. Our data showed that V27T is a good candidate to reduction the glutaminase activity, while has no remarkable effect on asparaginase activity of the enzyme. The simulation analysis revealed that V27T mutant is more stable than WT and mutant simulation was successful completely. QM-MM results confirmed the successfulness of our mutagenesis.

Identification of potent inhibitors of DNA methyltransferase 1 (DNMT1) through a pharmacophore-based virtual screening approach

DNA methylation is an epigenetic change that results in the addition of a methyl group at the carbon-5 position of cytosine residues. DNA methyltransferase (DNMT) inhibitors can suppress tumour growth and have significant therapeutic value. However, the established inhibitors are limited in their application due to their substantial cytotoxicity. Additionally, the standard drugs for DNMT inhibition are non-selective cytosine analogues with considerable cytotoxic side-effects. In the present study, we have designed a workflow by integrating various ligand-based and structure-based approaches to discover new agents active against DNMT1. We have derived a pharmacophore model with the help of available DNMT1 inhibitors. Utilising this model, we performed the virtual screening of Maybridge chemical library and the identified hits were then subsequently filtered based on the Naïve Bayesian classification model. The molecules that have returned from this classification model were subjected to ensemble based docking. We have selected 10 molecules for the biological assay by inspecting the interactions portrayed by these molecules. Three out of the ten tested compounds have shown DNMT1 inhibitory activity. These compounds were also found to demonstrate potential inhibition of cellular proliferation in human breast cancer MDA-MB-231 cells. In the present study, we have utilized a multi-step virtual screening protocol to identify inhibitors of DNMT1, which offers a starting point to develop more potent DNMT1 inhibitors as anti-cancer agents.

Analysis of positions and substituents on genotoxicity of fluoroquinolones with quantitative structure-activity relationship and 3D Pharmacophore model

The genotoxicity values of 21 quinolones were studied to establish a quantitative structure-activity relationship model and 3D Pharmacophore model separately for screening essential positions and substituents that contribute to genotoxicity of fluoroquinolones (FQs). A full factor experimental design was performed to analyze the specific main effect and second-order interaction effect of different positions and substituents on genotoxicity, forming a reasonable modification scheme which was validated on typical FQ with genotoxicity and efficacy data. Four positions (1, 5, 7, 8) were screened finally to form the full factorial experimental design which contained 72 congeners in total, illustrating that: the dominant effect of 5 and 7-positions on genotoxicity of FQs is main effect; meanwhile the effect of 1 and 8-positions is a second-order interaction effect; two adjacent positions always have stronger second-order interaction effect and lower genotoxicity; the obtained modification scheme had been validated on typical FQ congeners with the modified compound has a lower genotoxicity, higher synthesis feasibilities and efficacy.

Design, synthesis, molecular modeling and anti-hyperglycemic evaluation of novel quinoxaline derivatives as potential PPARγ and SUR agonists

In our effort to develop potent anti-hyperglycemic agents with potential agonistic activities toward PPARγ and SUR, three novel series of quinoxaline derivatives bearing sulfonylurea or sulfonylthiourea moieties with different linkers were designed and synthesized. Some of the newly synthesized compounds were evaluated in vivo for their anti-hyperglycemic activities in STZ-induced hyperglycemic rats. Compounds 15_a, 15_e, 19_b and 24_a exhibited the highest anti-hyperglycemic activities with % reduction in blood glucose level of (50.58, 43.84, 45.10 and 49.62, respectively). Additionally, eight compounds revealed potent anti-hyperglycemic activities were further evaluated in vitro for their PPARγ binding affinity and insulin-secreting ability as potential mechanisms for anti-hyperglycemic activity. Four compounds (15_a, 15_b, 15_d and 15_e) significantly bound to PPARγ with IC₅₀ values of 0.482, 0.491, 0.350 and 0.369μM, respectively. Moreover, Compounds 15_a and 15_b have demonstrated induction of insulin-secretion with EC₅₀ values of 0.92 and 0.98μM, respectively. Furthermore, molecular docking and pharmacophore generation techniques were carried out to investigate binding patterns and fit values of the designed compounds with PPARγ and SUR, respectively.

Discovery of potent inhibitors targeting Vibrio harveyi LuxR through shape and e-pharmacophore based virtual screening and its biological evaluation

Quorum sensing is widely recognized as an efficient mechanism in the regulation and production of several virulence factors, biofilm formation and stress responses. For this reason, quorum sensing circuit is emerging as a novel drug target for the development of anti-infective. Recently, cinnamaldehyde derivatives have been found to interfere with master quorum sensing transcriptional regulator and thereby decreasing the DNA binding ability of LuxR. However, the exact mode of cinnamaldehyde binding with LuxR and receptor interaction still remains inconclusive. In the current study, combined method of molecular docking and molecular dynamics simulations were performed to investigate the binding mode, dynamic and energy aspects of cinnamaldehyde derivatives into the binding site of LuxR. Based on the experimental and computational evidences, LuxR-3,4-dichloro-cinnamaldehyde complex was chosen for the development of e-pharmacophore model. Further, shape and e-pharmacophore based virtual screening were performed against ChemBridge database to find potent and suitable ligands for LuxR. By comparing the results of shape and e-pharmacophore based virtual screening; best 9 hit molecules were selected for further studies including ADMET prediction, molecular dynamics simulations and Prime MM-GBSA calculations. From the 9 hit molecules, the top most compound 3-(2,4-dichlorophenyl)-1-(1H-pyrrol-2-yl)-2-propen-1-one (ChemBridge-7364106) was selected for in vitro assays using Vibrio harveyi. The result revealed that ChemBridge-7364106 significantly reduced the bioluminescence production in a dose dependent manner. In addition, ChemBridge-7364106 showed a significant inhibition in biofilm formation and motility in V. harveyi. The results from the study suggest that ChemBridge-7364106 could serve as an anti-quorum sensing molecule for V. harveyi.

3D pharmacophore-based virtual screening, docking and density functional theory approach towards the discovery of novel human epidermal growth factor receptor-2 (HER2) inhibitors

Human epidermal growth factor receptor 2 (HER2) is one of the four members of the epidermal growth factor receptor (EGFR) family and is expressed to facilitate cellular proliferation across various tissue types. Therapies targeting HER2, which is a transmembrane glycoprotein with tyrosine kinase activity, offer promising prospects especially in breast and gastric/gastroesophageal cancer patients. Persistence of both primary and acquired resistance to various routine drugs/antibodies is a disappointing outcome in the treatment of many HER2 positive cancer patients and is a challenge that requires formulation of new and improved strategies to overcome the same. Identification of novel HER2 inhibitors with improved therapeutics index was performed with a highly correlating (r=0.975) ligand-based pharmacophore model (Hypo1) in this study. Hypo1 was generated from a training set of 22 compounds with HER2 inhibitory activity and this well-validated hypothesis was subsequently used as a 3D query to screen compounds in a total of four databases of which two were natural product databases. Further, these compounds were analyzed for compliance with Veber's drug-likeness rule and optimum ADMET parameters. The selected compounds were then subjected to molecular docking and Density Functional Theory (DFT) analysis to discern their molecular interactions at the active site of HER2. The findings thus presented would be an important starting point towards the development of novel HER2 inhibitors using well-validated computational techniques.

Modification of PBDEs (BDE-15, BDE-47, BDE-85 and BDE-126) biological toxicity, bio-concentration, persistence and atmospheric long-range transport potential based on the pharmacophore modeling assistant with the full factor experimental design

In this study, the properties of AhR binding affinity, bio-concentration factor, half-life and vapor pressure were selected as the typical indicators of biological toxicity, bio-concentration, persistence and atmospheric long-range transport potential for polybrominated diphenyl ethers (PBDEs), respectively. A three-dimensional pharmacophore modeling assistant with a full factor experimental design for each property was used to reveal the significant pharmacophore features and the substituent effects to obtain reasonable modified schemes for the selected target PBDEs. Finally, the performances of the persistent organic pollutant (POP) properties, the synthesis feasibility and the fire resistance of the modified compounds were evaluated. The most influential pharmacophore feature for all POP properties was the hydrophobic group, especially the vinyl and propyl groups. Modified compounds with two additional hydrophobic groups exhibited a better regulatory performance. The average reduction in the proportions of the four POP properties for the modified compounds (except for 3-phenyl-BDE-15) was 70.60%, 52.44%, 47.04% and 70.88%. In addition, the energy and the C-Br bond dissociation enthalpy of the four typical PBDEs were higher than those of the modified compounds (except for 3-phenyl-BDE-15), indicating the synthesis feasibility and the lower energy barrier of the modified compounds to release Br free radicals to provide fire resistance.

Identification of Structurally Diverse Antimicrobials Through Sequential Application of Pharmacophore Modeling, Virtual Screening, Molecular Docking and In Vitro Microbiological Assay

Dihydrofolate reductase enzyme has been an attractive biological target for the design and development of antimicrobials. Considering this, we have attempted to identify novel dihydrofolate reductase inhibitors through our well-defined in silico and in vitro work flow. An accurate and predictive pharmacophore model comprising of one hydrogen bond acceptor, two hydrophobic and one ring aromatic was developed and utilized as a query to search the National Cancer Institute and Maybridge database leading to retrieval of various compounds which were filtered on the basis of estimated activity, fit value and Lipinski's violation. Selected hits NSC3423, KM09759, NSC391, NSC2091 and HTS00630 were subjected to docking studies which resulted into visualization of potential interaction capabilities of hits in line to pharmacophoric features. The identified hits were evaluated for in vitro antimicrobial potential, and the results revealed that among all the five hits, NSC3423 is the most potent compound with activity against E. coli, P. aeruginosa, S. aureus, B. substilis, A. niger and F. oxysporum. On the other hand, KM09759, NSC391, NSC2091 and HTS00630 showed varying degree of activities against gram-positive, gram-negative and fungal strains.

Discovery of vascular endothelial growth factor receptor tyrosine kinase inhibitors by quantitative structure–activity relationships, molecular dynamics simulation and free energy calculation

Employing the combined strategy to understand the features of KDR–ligands complexes, and provide a basis for rational design of inhibitors.

Identification of potential CCR5 inhibitors through pharmacophore-based virtual screening, molecular dynamics simulation and binding free energy analysis

Employing the combined strategy to identify novel CCR5 inhibitors and provide a basis for rational drug design.

In silico and in vitro screening to identify structurally diverse non-azole CYP51 inhibitors as potent antifungal agent

The problem of resistance to azole class of antifungals is a serious cause of concern to the medical fraternity and thus there is an urgent need to identify non-azole scaffolds with high affinity for lanosterol 14α-demethylase (CYP51). In view of this we have attempted to identify novel non-azole CYP51 inhibitors through the application of pharmacophore based virtual screening and in vitro evaluation. A rigorously validated pharmacophore model comprising of 2 hydrogen bond acceptor and 2 hydrophobic features has been developed and used to mine NCI database. Out of 265 retrieved hits, NSC 1215 and 1520 have been chosen on the basis of Lipinski's rule of five, fit and estimated values. Both the hits were docked into the active site of CYP51. In view of high fit value and CDocker score, NSC 1215 and 1520 have been subjected to in vitro microbiological assay. The result reveals that NSC 1215 and 1520 are active against Candida albicans, Candida parapsilosis, Candida tropicalis, and Aspergillus niger. In addition to this the absorption characteristics of both the hits have also been determined using the rat sac technique and permeation in order of NSC 1520>NSC 1215 has been observed.

Discovery of a selective, safe and novel anti-malarial compound with activity against chloroquine resistant strain of Plasmodium falciparum

In recent years the DNA minor groove has attracted much attention for the development of anti-malarial agents. In view of this we have attempted to discover novel DNA minor groove binders through in-silico and in-vitro workflow. A rigorously validated pharmacophore model comprising of two positive ionizable (PI), one hydrophobic (HY) and one ring aromatic (RA) features was used to mine NCI chemical compound database. This led to retrieval of many hits which were screened on the basis of estimated activity, fit value and Lipinski's violation. Finally two compounds NSC639017 and NSC371488 were evaluated for their in-vitro anti-malarial activities against Plasmodium falciparum 3D7 (CQ sensitive) and K1 (CQ resistant) strains by SYBR green-I based fluorescence assay. The results revealed that out of two, NSC639017 posses excellent anti-malarial activity particularly against chloroquine resistant strain and moreover NSC639017 also appeared to be safe (CC50 126.04 μg/ml) and selective during cytotoxicity evaluation.

Combined pharmacophore modeling, 3D-QSAR, homology modeling and docking studies on CYP11B1 inhibitors

The mitochondrial cytochrome P450 enzymes inhibitor steroid 11β-hydroxylase (CYP11B1) can decrease the production of cortisol. Therefore, these inhibitors have an effect in the treatment of Cushing’s syndrome. A pharmacophore model generated by Genetic Algorithm with Linear Assignment for Hypermolecular Alignment of Datasets (GALAHAD) was used to align the compounds and perform comparative molecular field analysis (CoMFA) with Q² = 0.658, R² = 0.959. The pharmacophore model contained six hydrophobic regions and one acceptor atom, and electropositive and bulky substituents would be tolerated at the A and B sites, respectively. A three-dimensional quantitative structure-activity relationship (3D-QSAR) study based on the alignment with the atom root mean square (RMS) was applied using comparative molecular field analysis (CoMFA) with Q² = 0.666, R² = 0.978, and comparative molecular similarity indices analysis (CoMSIA) with Q² = 0.721, R² = 0.972. These results proved that all the models have good predictability of the bioactivities of inhibitors. Furthermore, the QSAR models indicated that a hydrogen bond acceptor substituent would be disfavored at the A and B groups, while hydrophobic groups would be favored at the B site. The three-dimensional (3D) model of the CYP11B1 was generated based on the crystal structure of the CYP11B2 (PDB code 4DVQ). In order to probe the ligand-binding modes, Surflex-dock was employed to dock CYP11B1 inhibitory compounds into the active site of the receptor. The docking result showed that the imidazolidine ring of CYP11B1 inhibitors form H bonds with the amino group of residue Arg155 and Arg519, which suggested that an electronegative substituent at these positions could enhance the activities of compounds. All the models generated by GALAHAD QSAR and Docking methods provide guidance about how to design novel and potential drugs for Cushing’s syndrome treatment.

An in silico protocol for identifying potential poly(ADP-ribose)polymerase-1 (PARP-1) inhibitors from chemical databases

Pharmacophore models, steric constriction and docking approaches have been employed in the identification of potential PARP-1 inhibitors from databases.

Establishment of a screening protocol for identification of aminopeptidase N inhibitors

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Two pharmacophore models have been developed.

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Virtual screening was performed by the pharmacophore models and docking.

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Six selected hits were discovered to have inhibitory activities.

Inhibitors of aminopeptidase N (APN) have been thought as potential drugs for the treatment of tumor angiogenesis, invasion and metastasis and a considerable number of APN inhibitors have been reported recently. To clarify the essential structure–activity relationship for the APN inhibitors as well as identify new potent leads against APN, pharmacophore models were established using structure- and common feature-based approaches and validated with a database of active and inactive compounds. These validated pharmacophores were then used in database screening for novel virtual leads. The hit compounds were further subjected to molecular docking studies to refine the retrieved hits. Finally, six structurally diverse compounds that showed strong interactions with the key amino acids and the zinc ion were selected for biological evaluation, where two hits showed more than 70% inhibition against APN at 60 μM concentration. The evaluation results show the potential of our screening approach in identifying APN inhibitors.

Expression of recombinant human mast cell chymase with Asn-linked glycans in glycoengineered Pichia pastoris

Recombinant human mast cell chymase (rhChymase) was expressed in secreted form as an active enzyme in the SuperMan5 strain of GlycoSwitch® Pichia pastoris, which is engineered to produce proteins with (Man)5(GlcNAc)2 Asn-linked glycans. Cation exchange and heparin affinity chromatography yielded 5mg of active rhChymase per liter of fermentation medium. Purified rhChymase migrated on SDS-PAGE as a single band of 30 kDa and treatment with peptide N-glycosidase F decreased this to 25 kDa, consistent with the established properties of native human chymase (hChymase). Polyclonal antibodies against hChymase detected rhChymase by Western blot. Active site titration with Eglin C, a potent chymase inhibitor, quantified the concentration of purified active enzyme. Kinetic analyses with succinyl-Ala-Ala-Pro-Phe (suc-AAPF) p-nitroanilide and thiobenzyl ester synthetic substrates showed that heparin significantly reduced KM, whereas heparin effects on kcat were minor. Pure rhChymase with Asn-linked glycans closely resembles hChymase. This bioengineering approach avoided hyperglycosylation and provides a source of active rhChymase for other studies as well as a foundation for production of recombinant enzyme with human glycosylation patterns.

Tubulin inhibitors: pharmacophore modeling, virtual screening and molecular docking

AIM

To construct a quantitative pharmacophore model of tubulin inhibitors and to discovery new leads with potent antitumor activities.

METHODS

Ligand-based pharmacophore modeling was used to identify the chemical features responsible for inhibiting tubulin polymerization. A set of 26 training compounds was used to generate hypothetical pharmacophores using the HypoGen algorithm. The structures were further validated using the test set, Fischer randomization method, leave-one-out method and a decoy set, and the best model was chosen to screen the Specs database. Hit compounds were subjected to molecular docking study using a Molecular Operating Environment (MOE) software and to biological evaluation in vitro.

RESULTS

Hypo1 was demonstrated to be the best pharmacophore model that exhibited the highest correlation coefficient (0.9582), largest cost difference (70.905) and lowest RMSD value (0.6977). Hypo1 consisted of one hydrogen-bond acceptor, a hydrogen-bond donor, a hydrophobic feature, a ring aromatic feature and three excluded volumes. Hypo1 was validated with four different methods and had a goodness-of-hit score of 0.81. When Hypo1 was used in virtual screening of the Specs database, 952 drug-like compounds were revealed. After docking into the colchicine-binding site of tubulin, 5 drug-like compounds with the required interaction with the critical amino acid residues and the binding free energies < -4 kcal/mol were selected as representative leads. Compounds 1 and 3 exhibited inhibitory activity against MCF-7 human breast cancer cells in vitro.

CONCLUSION

Hypo1 is a quantitative pharmacophore model for tubulin inhibitors, which not only provides a better understanding of their interaction with tubulin, but also assists in discovering new potential leads with antitumor activities.

Pharmacophore based virtual screening, molecular docking and biological evaluation to identify novel PDE5 inhibitors with vasodilatory activity

Prompted by the role of PDE5 and its closely associated cAMP and cGMP in hypertension, we have attempted to discover novel PDE5 inhibitors through ligand based virtual screening. Rigorously validated model comprising of one HBA, one HY and one RA was used as a query to search the NCI database leading to retrieval of many compounds which were screened on the basis of estimated activity, fit value and Lipinski's violation. Selected compounds were subjected to docking studies which resulted into visualization of potential interaction capabilities of NCI compounds in line to pharmacophoric features. Finally three compounds were subjected to in vitro evaluation using the isolated rat aortic model. The results showed that all three compounds are potent and novel PDE5 inhibitors with vasodilatory activity range from 10(-2) to 10(-5) M.

Pharmacophore modeling and virtual screening for the discovery of new type 4 cAMP phosphodiesterase (PDE4) inhibitors

Type 4 cAMP phosphodiesterase (PDE4) inhibitors show a broad spectrum of anti-inflammatory effects in almost all kinds of inflamed cells, by an increase in cAMP levels which is a pivotal second messenger responsible for various biological processes. These inhibitors are now considered as the potential drugs for treatment of chronic inflammatory diseases. However, some recently marketed inhibitors e.g., roflumilast, have shown adverse effects such as nausea and emesis, thus restricting its use. In order to identify novel PDE4 inhibitors with improved therapeutic indexes, a highly correlating (r = 0.963930) pharmacophore model (Hypo1) was established on the basis of known PDE4 inhibitors. Validated Hypo1 was used in database screening to identify chemical with required pharmacophoric features. These compounds are further screened by using the rule of five, ADMET and molecular docking. Finally, twelve hits which showed good results with respect to following properties such as estimated activity, calculated drug-like properties and scores were proposed as potential leads to inhibit the PDE4 activity. Therefore, this study will not only assist in the development of new potent hits for PDE4 inhibitors, but also give a better understanding of their interaction with PDE4. On a wider scope, this will be helpful for the rational design of novel potent enzyme inhibitors.

Pharmacophore modelling and electronic feature analysis of hydroxamic acid derivatives, the HIV integrase inhibitors

Hydroxamic acid derivatives with metal ion binding properties were collected from the literature to generate a pharmacophore and 3D-QSAR model for HIV strand transfer inhibition. The derived pharmacophore model (AAAHRR) recognizes both metal ion binding site and hydrophobic group. The QSAR model generated using this hypothesis expressed statistical significance (r(2) = 0.971 for the training set and q(2) = 0.913 for the test set). The ability of this pharmacophore model to retrieve other metal ion binding inhibitors was examined by screening the ChemBank database (ligandinfo) incorporated with 10 known strand transfer inhibitors. The studied favourable and unfavourable contours of chemical features (H-bond donor, acceptor and hydrophobic sites) revealed the role of hydrophobic substitution at the fluorobenzene ring and cyclization of the metal ion binding hydroxamic acid in effective integrase inhibition. Analysis of the frontier orbitals, HOMO and LUMO revealed that the nucleophilic / electrophilic interactions depend on the significant overlapping observed at the azaindole and hydroxamic acid groups. In essence, the generated pharmacophore model is competent enough to disclose the essential site-specific interactions involved in the inhibition of HIV integrase, and hence can be used in virtual screening to identify novel scaffolds as leads with increased anti-viral potency.

A combination of receptor-based pharmacophore modeling & QM techniques for identification of human chymase inhibitors

Inhibition of chymase is likely to divulge therapeutic ways for the treatment of cardiovascular diseases, and fibrotic disorders. To find novel and potent chymase inhibitors and to provide a new idea for drug design, we used both ligand-based and structure-based methods to perform the virtual screening(VS) of commercially available databases. Different pharmacophore models generated from various crystal structures of enzyme may depict diverse inhibitor binding modes. Therefore, multiple pharmacophore-based approach is applied in this study. X-ray crystallographic data of chymase in complex with different inhibitors were used to generate four structure-based pharmacophore models. One ligand-based pharmacophore model was also developed from experimentally known inhibitors. After successful validation, all pharmacophore models were employed in database screening to retrieve hits with novel chemical scaffolds. Drug-like hit compounds were subjected to molecular docking using GOLD and AutoDock. Finally four structurally diverse compounds with high GOLD score and binding affinity for several crystal structures of chymase were selected as final hits. Identification of final hits by three different pharmacophore models necessitates the use of multiple pharmacophore-based approach in VS process. Quantum mechanical calculation is also conducted for analysis of electrostatic characteristics of compounds which illustrates their significant role in driving the inhibitor to adopt a suitable bioactive conformation oriented in the active site of enzyme. In general, this study is used as example to illustrate how multiple pharmacophore approach can be useful in identifying structurally diverse hits which may bind to all possible bioactive conformations available in the active site of enzyme. The strategy used in the current study could be appropriate to design drugs for other enzymes as well.

Molecular modeling study for inhibition mechanism of human chymase and its application in inhibitor design

Human chymase catalyzes the hydrolysis of peptide bonds. Three chymase inhibitors with very similar chemical structures but highly different inhibitory profiles towards the hydrolase function of chymase were selected with the aim of elucidating the origin of disparities in their biological activities. As a substrate (angiotensin-I) bound crystal structure is not available, molecular docking was performed to dock the substrate into the active site. Molecular dynamics simulations of chymase complexes with inhibitors and substrate were performed to calculate the binding orientation of inhibitors and substrate as well as to characterize conformational changes in the active site. The results elucidate details of the 3D chymase structure as well as the importance of K40 in hydrolase function. Binding mode analysis showed that substitution of a heavier Cl atom at the phenyl ring of most active inhibitor produced a great deal of variation in its orientation causing the phosphinate group to interact strongly with residue K40. Dynamics simulations revealed the conformational variation in region of V36-F41 upon substrate and inhibitor binding induced a shift in the location of K40 thus changing its interactions with them. Chymase complexes with the most active compound and substrate were used for development of a hybrid pharmacophore model which was applied in databases screening. Finally, hits which bound well at the active site, exhibited key interactions and favorable electronic properties were identified as possible inhibitors for chymase. This study not only elucidates inhibitory mechanism of chymase inhibitors but also provides key structural insights which will aid in the rational design of novel potent inhibitors of the enzyme. In general, the strategy applied in the current study could be a promising computational approach and may be generally applicable to drug design for other enzymes.

An innovative strategy for dual inhibitor design and its application in dual inhibition of human thymidylate synthase and dihydrofolate reductase enzymes

Due to the diligence of inherent redundancy and robustness in many biological networks and pathways, multitarget inhibitors present a new prospect in the pharmaceutical industry for treatment of complex diseases. Nevertheless, to design multitarget inhibitors is concurrently a great challenge for medicinal chemists. We have developed a novel computational approach by integrating the affinity predictions from structure-based virtual screening with dual ligand-based pharmacophore to discover potential dual inhibitors of human Thymidylate synthase (hTS) and human dihydrofolate reductase (hDHFR). These are the key enzymes in folate metabolic pathway that is necessary for the biosynthesis of RNA, DNA, and protein. Their inhibition has found clinical utility as antitumor, antimicrobial, and antiprotozoal agents. A druglike database was utilized to perform dual-target docking studies. Hits identified through docking experiments were mapped over a dual pharmacophore which was developed from experimentally known dual inhibitors of hTS and hDHFR. Pharmacophore mapping procedure helped us in eliminating the compounds which do not possess basic chemical features necessary for dual inhibition. Finally, three structurally diverse hit compounds that showed key interactions at both active sites, mapped well upon the dual pharmacophore, and exhibited lowest binding energies were regarded as possible dual inhibitors of hTS and hDHFR. Furthermore, optimization studies were performed for final dual hit compound and eight optimized dual hits demonstrating excellent binding features at target systems were also regarded as possible dual inhibitors of hTS and hDHFR. In general, the strategy used in the current study could be a promising computational approach and may be generally applicable to other dual target drug designs.