Discovery of novel Akt1 inhibitors by an ensemble-based virtual screening method, molecular dynamics simulation, and in vitro biological activity testing.

Akt1, as an important member of the Akt family, plays a controlled role in cancer cell growth and survival. Inhibition of Akt1 activity can promote cancer cell apoptosis and inhibit tumor growth. Therefore, in this investigation, a multilayer virtual screening approach, including receptor-ligand interaction-based pharmacophore, 3D-QSAR, molecular docking, and deep learning methods, was utilized to construct a virtual screening platform for Akt1 inhibitors. 17 representative compounds with different scaffolds were identified as potential Akt1 inhibitors from three databases. Among these 17 compounds, the Hit9 exhibited the best inhibitory activity against Akt1 with inhibition rate of 33.08% at concentration of 1 µM. The molecular dynamics simulations revealed that Hit9 and Akt1 could form a compact and stable complex. Moreover, Hit9 interacted with some key residues by hydrophobic, electrostatic, and hydrogen bonding interactions and induced substantial conformation changes in the hinge region of the Akt1 active site. The average binding free energies for the Akt1-CQU, Akt1-Ipatasertib, and Akt1-Hit9 systems were - 34.44, - 63.37, and - 39.14 kJ mol-1, respectively. In summary, the results obtained in this investigation suggested that Hit9 with novel scaffold may be a promising lead compound for developing new Akt1 inhibitor for treatment of various cancers with Akt1 overexpressed.

Multi-process regulation of novel brominated flame retardants: Environmentally friendly substitute design, screening and environmental risk regulation.

Novel brominated flame retardants (NBFRs), one of the most widely used synthetic flame-retardant materials, have been considered as a new group of pollutants that potentially affect human health. To overcome the adverse effects of NBFRs, a systematic approach for molecular design, screening, and performance evaluation was developed to generate environmentally friendly NBFR derivatives with unaltered functionality. In the present study, the features of NBFRs (long-distance migration, biotoxicity, bioenrichment, and environmental persistence) were determined and characterized by the multifactor comprehensive characterization method with equal weight addition, and the similarity index analysis (CoMSIA) model was constructed. Based on the three-dimensional equipotential diagram of the target molecule 2-ethylhexyl tetrabromobenzoic acid (TBB), 23 TBB derivatives were designed. Of these, 22 derivatives with decreased environmental impact and unaltered functional properties (i.e., flame retardancy and stability) were selected using 3D-QSAR models and density functional theory methods. The health risks of these derivatives to humans were assessed by toxicokinetic analysis; the results narrowed down the number of candidates to three (Derivative-7, Derivative-10, and Derivative-15). The environmental impact of these candidates was further evaluated and regulated in the real-world environment by using molecular dynamics simulation assisted by the Taguchi experimental design method. The relationship between the binding effects and the nonbonding interaction resultant force (TBB derivatives-receptor proteins) was also studied, and it was found that the larger the modulus of the binding force, the stronger the binding ability of the two. This finding indicated that the environmental impact of the designed NBFR derivatives was decreased. The present study aimed to provide a new idea and method for designing NBFR substitutes and to provide theoretical support for restraining the potential environmental risks of NBFRs.

Screening of Oral Potential Angiotensin-Converting Enzyme Inhibitory Peptides from Zizyphus jujuba Proteins Based on Gastrointestinal Digestion In Vivo.

Plant proteins are a good source of active peptides, which can exert physiological effects on the body. Predicting the possible activity of plant proteins and obtaining active peptides with oral potential are challenging. In this study, the potential activity of peptides from Zizyphus jujuba proteins after in silico simulated gastrointestinal digestion was predicted using the BIOPEP-UWM™ database. The ACE-inhibitory activity needs to be further investigated. The actual peptides in mouse intestines after the oral administration of Zizyphus jujuba protein were collected and analyzed, 113 Zizyphus jujuba peptides were identified, and 3D-QSAR models of the ACE-inhibitory activity were created and validated using a training set (34 peptides) and a test set (12 peptides). Three peptides, RLPHV, TVKPGL and KALVAP, were screened using the 3D-QSAR model and were found to bind to the active sites of the ACE enzyme, and their IC50 values were determined. Their values were 6.01, 3.81, and 17.06 µM, respectively. The in vitro digestion stabilities of the RLPHV, TVKPGL, and KALVAP peptides were 82%, 90%, and 78%. This article provides an integrated method for studying bioactive peptides derived from plant proteins.

4-Phthalimidobenzenesulfonamide Derivatives as Acetylcholinesterase and Butyrylcholinesterase Inhibitors: DFTs, 3D-QSAR, ADMET, and Molecular Dynamics Simulation.

INTRODUCTION: Alzheimer's disease is a form of dementia which affects majority of the people. It is characterized by memory loss and other cognitive function disabilities and is one of the most challenging neurodegenerative disorders to treat because of its progressive nature. The disease affects millions of people all around the world, and the number of those affected is expanding every day. In the previous study, the 4-phthalimidobenzenesulfonamide derivatives were synthesized as AChE and BChE inhibitors, and here, we were aiming to further reporting in silico studies of these compounds for efficient drug discovery process and to find out the potential lead compounds. METHODS: In silico characterization included density functional theory (DFT) studies, 3D-QSAR, ADMET properties, molecular docking, and molecular dynamic simulations. The geometries of all derivatives were optimized using B3LYP method and 6-311G basis set. RESULTS: The findings of the current study revealed that 4-phthalimidobenzenesulfonamide derivatives exhibited a reactive electronic property which is essential for anticholinesterase activity. Moreover, optimized structures were subjected to molecular docking studies with targeted protein. The compounds 2c and 2g showed excellent binding score of -37.44 and -33.67 kJ/mol with BChE and AChE, respectively, and exhibited strong binding affinity. The potent derivatives produced stable complex with amino acid residues of active pocket of both BChE and AChE. The stability of protein-ligand complexes was determined by molecular dynamic simulation studies, and results were found in correlation with molecular docking findings. CONCLUSION: Findings of the current study suggested that these derivatives are potent inhibitors of cholinesterase enzyme.

Identifying Novel ATX Inhibitors via Combinatory Virtual Screening Using Crystallography-Derived Pharmacophore Modelling, Docking Study, and QSAR Analysis.

Autotaxin (ATX) is considered as an interesting drug target for the therapy of several diseases. The goal of the research was to detect new ATX inhibitors which have novel scaffolds by using virtual screening. First, based on two diverse receptor-ligand complexes, 14 pharmacophore models were developed, and the 14 models were verified through a big test database. Those pharmacophore models were utilized to accomplish virtual screening. Next, for the purpose of predicting the probable binding poses of compounds and then carrying out further virtual screening, docking-based virtual screening was performed. Moreover, an excellent 3D QSAR model was established, and 3D QSAR-based virtual screening was applied for predicting the activity values of compounds which got through the above two-round screenings. A correlation coefficient r2, which equals 0.988, was supplied by the 3D QSAR model for the training set, and the correlation coefficient r2 equaling 0.808 for the test set means that the developed 3D QSAR model is an excellent model. After the filtering was done by the combinatory virtual screening, which is based on the pharmacophore modelling, docking study, and 3D QSAR modelling, we chose nine potent inhibitors with novel scaffolds finally. Furthermore, two potent compounds have been particularly discussed.

Design, synthesis and biological evaluation of amide-pyridine derivatives as novel dual-target (SE, CYP51) antifungal inhibitors.

Based on the analysis of the squalene cyclooxygenase (SE) and 14α-demethylase (CYP51) inhibitors pharmacophore feature and the dual-target active sites, a series of compounds with amide-pyridine scaffolds have been designed and synthesized to treat the increasing incidence of drug-resistant fungal infections. In vitro evaluation showed that these compounds have a certain degree of antifungal activity. The most potent compounds 11a, 11b with MIC values in the range of 0.125-2 µg/ml had a broad-spectrum antifungal activity and exhibited excellent inhibitory activity against drug-resistant pathogenic fungi. Preliminary mechanism studies revealed that the compound 11b might play an antifungal role by inhibiting the activity of SE and CYP51. Notably compounds did not show the genotoxicity through plasmid binding assay. Finally, this study of molecular docking, ADME/T prediction and the construction of 3D QSAR model were performed. These results can point out the direction for further optimization of the lead compound.

Multistage in silico approach to identify novel quinoline derivatives as potential c-kit kinase inhibitors.

The type II-C-KIT signaling network has been extensively studied for its potential as a target for cancer treatment, leading to the investigation of quinoline derivatives as compounds with inhibitory effects on c-Kit kinase. In this study, a multistage approach was employed, including the creation of pharmacophore models, 3D QSAR analysis, virtual screening, docking investigations, and molecular dynamics stimulation. The pharmacophore evaluation included a data set of 29 ligands, which resulted in the generation of the ADDHR_1pharmacophore model as the most promising, with a survival score of 5.6812. The main objective was to utilize the atom-based 3D-QSAR approach for generating robust 3D-QSAR models aimed at identifying new TypeII-C-kit kinase inhibitors. The evaluations of these models have convincingly demonstrated their high predictive power (Q2 = 0.6547, R2 = 0.9947). Using atom-based 3D-QSAR data, a total of 7564 novel compounds were generated from R-group enumeration. Molecular docking and MM-GBSA study revealed that compound A1 exhibited the highest binding score of -9.30 kcal/mol and a Δ GBind value of -90.56 kcal/mol. The ZINC compounds were then screened using the pharmacophore model, followed by virtual screening, which identified ZINC65798256, ZINC09317958, ZINC73187176, and ZINC76176670 as potential candidates with promising docking scores. Among these, ZINC65798256 demonstrated the best binding interactions with amino acid residues, ASP810, LYS623, CYS673, and THR670 (PDB ID: 1T46). To further analyze the structural features and molecular interactions, molecular dynamics simulation was conducted for a time scale of 100 ns.Communicated by Ramaswamy H. Sarma.

Integrated virtual screening and in vitro studies for exploring the mechanism of triterpenoids in Chebulae Fructus alleviating mesaconitine-induced cardiotoxicity via TRPV1 channel.

Background: In traditional Mongolian or Tibetan medicine in China, Chebulae Fructus (CF) is widely used to process or combine with aconitums to decrease the severe toxicity of aconitums. Researches in this area have predominantly focused on tannins, with few research on other major CF components for cardiotoxicity mitigation. The present study aimed to clarify whether triterpenoids can attenuate the cardiotoxicity caused by mesaconitine (MA) and investigate the mechanism of cardiotoxicity attenuation. Methods: Firstly, the pharmacophore model, molecular docking, and 3D-QSAR model were used to explore the mechanism of CF components in reducing the toxicity of MA mediated by the TRPV1 channel. Then three triterpenoids were selected to verify whether the triterpenoids had the effect of lowering the cardiotoxicity of MA using H9c2 cells combined with MTT, Hoechst 33258, and JC-1. Finally, Western blot, Fluo-3AM, and MTT assays combined with capsazepine were used to verify whether the triterpenoids reduced H9c2 cardiomyocyte toxicity induced by MA was related to the TRPV1 channel. Results: Seven triterpenoids in CF have the potential to activate the TRPV1 channel. And they exhibited greater affinity for TRPV1 compared to other compounds and MA. However, their activity was relatively lower than that of MA. Cell experiments revealed that MA significantly reduced H9c2 cell viability, resulting in diminished mitochondrial membrane potential and nuclear pyknosis and damage. In contrast, the triterpenoids could improve the survival rate significantly and counteract the damage of MA to the cells. We found that MA, arjungenin (AR), and maslinic acid (MSA) except corosolic acid (CRA) upregulated the expression of TRPV1 protein. MA induced a significant influx of calcium, whereas all three triterpenoids alleviated this trend. Blocking the TRPV1 channel with capsazepine only increased the cell viability that had been simultaneously treated with MA, and AR, or MSA. However, there was no significant difference in the CRA groups treated with or without capsazepine. Conclusion: The triterpenoids in CF can reduce the cardiotoxicity caused by MA. The MSA and AR function as TRPV1 agonists with comparatively reduced activity but a greater capacity to bind to TRPV1 receptors, thus antagonizing the excessive activation of TRPV1 by MA.

Risk mitigation strategy and mechanism analysis of neonicotinoid pesticides on earthworms.

Neonicotinoid insecticides (NNIs) are a new class of widely used insecticides with certain risks to non-target organisms, like earthworms. The gray correlation method was used to calculate the comprehensive risk effect value of acute toxicity (LC50) and bioaccumulation (logKow) of NNIs on earthworms. A comprehensive effects three-dimensional quantitative structure-activity relationship (3D-QSAR) model was constructed, using NNIs molecular structures and the comprehensive effect value as the independent and dependent variables, respectively. One of the representatives guadipyr (GUA) was selected as the template molecule for the molecular design and modification. A total of 63 NNIs alternatives were designed with a reduced comprehensive value higher than 10%, and as high as 42%. After screening, 15 NNIs alternatives were screened with decreased acute toxicity to earthworms, bioaccumulation effects and improved functional property. The calculated primary acute risk quotient of earthworms shows that the designed NNIs alternatives have lower earthworm risks (reduction of 70.48-99.99%). Results also found that the electronic, geometric and topological parameters of NNIs are the key descriptors that affect NNIs alternatives' toxicity. The number of hydrophobic interaction amino acid residues in NNIs molecules also contributes to the acute toxicity and the bioaccumulation of NNIs alternatives on earthworms. This study aims to design and screen functionally improved and environmentally friendly NNIs alternatives that have low risk to earthworms and provide theoretical methods and new ideas for the risk control and development of pesticides represented by NNIs.

Computational approaches for the design of novel dopamine D2 and serotonin 5-HT2A receptor dual antagonist towards schizophrenia.

Piperidine and piperazine derivatives exhibit a diverse range of biological applications, including antipsychotic activity. In this study, a dataset of molecules containing piperidine, piperazine moieties that possess serotonin 5-HT2A and dopamine D2 inhibitory activity have been chosen for Pharmacophore modeling, Quantitative Structure-Activity (3D-QSAR) Relationship, Molecular docking, and ADME studies. The pharmacophoric hypothesis was found to be AAHPRRR_1 having seven features as one H-bond acceptor (A), one hydrophobic (H), one positive ion acceptor (P), and three aromatic rings (R), with survival score = 6.465 and AUC = 0.92. Based on the best hypothesis, the ZINC-Data base was virtually screened to find out the lead molecules. 3D-QSAR model, including internal and external validation showed comparative molecular field analysis (CoMFA) against 5HT2A (q 2 = 0.552, R 2 = 0.889, and r 2 poured. = 0.653 and number of component 5) and comparative molecular similarity indices analysis (CoMSIA) (q 2 = 0.599, R 2 = 0.893, and r 2 pred. = 0.617), for D2 (CoMFA, q 2 = 0.577, R 2 = 0.863, and r 2 pred. = 0.598) (CoMSIA, q 2 = 0.532, R 2 = 0.82) all results exhibited better productivity and significant statistical reliability of the model. The docking study was carried out on the crystal structure of 5-HT2A having PDB ID; 6A93 and D2 receptor having PDB ID; 6CM4. The screened compound ZINC74289318 possess a higher docking score - 10.744 and - 11.388 than co-crystallized ligand docking score - 8.840 and - 10.06 against 5-HT2A and D2 receptor respectively. Further, ZINC74289318 was screened for all drug-likeness parameters and no showed violation of the Lipinski rule of five. Also, it was found to possess good bioavailability of 0.55 with synthetic accessibility of 4.42 which is greater than risperidone.

3D-QSAR-aided toxicity assessment of synthetic musks and their transformation by-products.

Synthetic musks (SMs) are fragrance additives widely used in personal care products. SMs and their transformation by-products may reach the environment even after wastewater treatment, resulting in ecological and health concerns. The identification and toxicity assessment of SM by-products generated from different chemical and biological treatment processes have been rarely studied. This study established a 3D-QSAR model based on SMs' molecular structures (independent variable) and their lethal concentration (LC50) of mysid (dependent variable). The developed model was further used to predict the LC50 of SMs transformation by-products. Fifty-eight by-products of six common SMs (i.e., galaxolide (HHCB), tonalide (AHTN), phantolide (PHAN), traseolide (TRASE), celestolide (ADBI), and musk ketone (MK)) generated from biodegradation, photodegradation, advanced oxidation, and chlorination were identified through literature review and lab experiment as the model inputs. Predicted LC50 results indicated that the toxicity of 40% chlorination by-products is higher than their precursors. Biodegradation is an effective method to treat AHTN. The advanced oxidation may be the best way to treat HHCB. This is the first study on biotoxicity of SM transformation by-products predicted by the 3D-QSAR model. The research outputs helped to provide valuable reference data and guidance to improve management of SMs and other emerging contaminants.

Pharmacophore Generation, Quantitative Structure-Activity Relationship (QSAR), and Molecular Dynamic Simulation of Newly Substituted N-(6- Chloro-3-cyano-4-phenyl-4H-chromen-2-yl)-2-(4-chloro-phenoxy)-acetamide for Anticancer Activity.

OBJECTIVE: The main objective of the study was to develop the Quantitative Structure- Activity Relationship (QSAR) and pharmacophore model by using data obtained from HT-29 cells to develop potent lead molecule for the scientific community. MATERIALS AND METHODS: Common pharmacophore model, atom-based 3D-QSAR, and molecular dynamic (MD) simulation were carried out via computational techniques by using 4H-chromene derivatives. RESULTS: The reliable common pharmacophoric hypothesis, DHH13 was generated and 3.95 survival value was also found. Furthermore, the statistically significant 3D-QSAR model was developed where r2=0.52 was found by using the Partial least squares (PLS) regression method. Phase predicted activity and Log GI50 demonstrated an important atomic position in the structure of ligands to ascertain anti colon cancer activity. Also, MD simulation was carried out between top rank leads targeting IL-6 that provided better binding conformational and complex stability into the active pocket site of the target throughout the MD simulation. CONCLUSION: The outcome of this design shows that the pharmacophore model and 3D-QSAR might be helpful for researchers in the field of medicinal chemistry to design and develop potential anti colon cancer compounds.

Focus on Human Monoamine Transporter Selectivity. New Human DAT and NET Models, Experimental Validation, and SERT Affinity Exploration.

The most commonly used antidepressant drugs are the serotonin transporter inhibitors. Their effects depend strongly on the selectivity for a single monoamine transporter compared to other amine transporters or receptors, and the selectivity is roughly influenced by the spatial protein structure. Here, we provide a computational study on three human monoamine transporters, i.e., DAT, NET, and SERT. Starting from the construction of hDAT and hNET models, whose three-dimensional structure is unknown, and the prediction of the binding pose for 19 known inhibitors, 3D-QSAR models of three human transporters were built. The training set variability, which was high in structure and activity profile, was validated using a set of in-house compounds. Results concern more than one aspect. First of all, hDAT and hNET three-dimensional structures were built, validated, and compared to the hSERT one; second, the computational study highlighted the differences in binding site arrangement statistically correlated to inhibitor selectivity; third, the profiling of new inhibitors pointed out a conservation of the inhibitory activity trend between rabbit and human SERT with a difference of about 1 order of magnitude; fourth, binding and functional studies confirmed 4-(benzyloxy)-4-phenylpiperidine 20a-d and 21a-d as potent SERT inhibitors. In particular, one of the compounds (compound 20b) revealed a higher affinity for SERT than paroxetine in human platelets.

Environment-friendly PCN derivatives design and environmental behavior simulation based on a multi-activity 3D-QSAR model and molecular dynamics.

A multi-activity three-dimensional quantitative structure-activity relationship (3D-QSAR) model was established based on the comprehensive evaluation index (CEI) of polychlorinated naphthalenes (PCNs). The CEI values were calculated using the vector analysis method in combination with the following parameters: biological toxicity (predicted by logEC50), bioconcentration (predicted by logKow), long-distance migration (predicted by logPL), and biodegradation (predicted by total-score). Additionally, sixty-four CN-70 derivatives with lower CEI values were designed, among which three derivatives with reduced CEI values were selected for verification based on an evaluation of their persistent organic pollutant properties and practicability. Finally, an environmental behavior simulation was conducted via molecular dynamics simulation aided by the Taguchi experimental design by considering the degradation characteristics of the three aforementioned CN-70 derivatives as an example. Only two of the selected CN-70 derivatives were observed to be more easily degraded when compared with the CN-70 molecule (ascending range: 11.57 %-13.57 %) in a real-world setting, which was consistent with the biodegradability prediction results (ascending range: 14.94 %-22.49 %) obtained through the molecular docking studies. The multi-activity 3D-QSAR model established in this study overcame the limitations of generating molecular designs based on single-effect models from the source because it focused on the multiple effects of the pollutants.

Pharmacophore-enabled virtual screening, molecular docking and molecular dynamics studies for identification of potent and selective histone deacetylase 8 inhibitors.

Histone deacetylases (HDACs) play important roles in various biological processes, but are also notorious for their over-expression in numerous cancers and neurological disorders. Therefore, the development of isoform selective HDAC inhibitors is crucial in order to prevent any side effects of pan inhibition. This work focuses on identifying novel inhibitors for the selective inhibition of HDAC8, an isoform implicated in fatal diseases like T-cell lymphoma, colon cancer and childhood neuroblastoma. Virtual screening of the 'In-trials' subset of ZINC database has been carried out with the help of two pharmacophore models signifying potent and selective HDAC8 inhibition. A detailed molecular docking strategy, followed by molecular dynamics simulations and post-scoring with MM-GBSA calculations, has led to the identification of six promising molecules that have excellent binding with the HDAC8 active site. In order to establish the selectivity profile of these molecules, their binding to off-target HDAC isoforms has also been evaluated. Substitution analyses of the proposed inhibitors suggest that aromatic substituents that access the adjacent hydrophobic pocket of the HDAC8 active site have the potential to further enhance the HDAC8 selectivity.

Unraveling the molecular mechanism of benzothiophene and benzofuran scaffold-merged compounds binding to anti-apoptotic Myeloid cell leukemia 1.

Myeloid cell leukemia 1 (Mcl1), is an antiapoptotic member of the Bcl-2 family proteins, has gained considerable importance due to its overexpression activity prevents the oncogenic cells to undergo apoptosis. This overexpression activity of Mcl1 eventually develops strong resistance to a wide variety of anticancer agents. Therefore, designing novel inhibitors with potentials to elicit higher binding affinity and specificity to inhibit Mcl1 activity is of greater importance. Thus, Mcl1 acts as an attractive cancer target. Despite recent experimental advancement in the identification and characterization of benzothiophene and benzofuran scaffold-merged compounds, the molecular mechanisms of their binding to Mcl1 are yet to be explored. The current study demonstrates an integrated approach - pharmacophore-based 3D-QSAR, docking, molecular dynamics (MD) simulation and free-energy estimation - to access the precise and comprehensive effects of current inhibitors targeting Mcl1 together with its known activity values. The pharmacophore - ANRRR.240 - based 3D-QSAR model from the current study provided high confidence (R2=0.9154, Q2=0.8736 and RMSE = 0.3533) values. Furthermore, the docking correctly predicted the binding mode of highly active compound 42. Additionally, the MD simulation for docked complex under explicit-solvent conditions together with free-energy estimation exhibited stable interaction and binding strength over the time period. Also, the decomposition analysis revealed potential energy contributing residues - M231, M250, V253, R265, L267 and F270 - to the complex stability. Overall, the current investigation might serve as a valuable insight, either to (i) improve the binding affinity of the current compounds or (ii) discover new generation anticancer agents that can effectively downregulate Mcl1 activity. Communicated by Ramaswamy H. Sarma.

Hyphenated 3D-QSAR statistical model-drug repurposing analysis for the identification of potent neuraminidase inhibitor.

The Influenza A virus is one of the principle causes of respiratory illness in human. The surface glycoprotein of the influenza virus, neuraminidase (NA), has a vital role in the release of new viral particle and spreads infection in the respiratory tract. It has been long recognized as a valid drug target for influenza A virus infection. Oseltamivir is used as a standard drug of choice for the treatment of influenza. However, the emergence of mutants with novel mutations has increased the resistance to potent NA inhibitor. In the present investigation, we have employed computer-assisted combinatorial techniques in the screening of 8621 molecules from Drug Bank to find potent NA inhibitors. A three-dimensional pharmacophore model was generated from the previously reported 28 carbocylic influenza NA inhibitors along with oseltamivir using PHASE module of Schrödinger Suite. The model generated consists of one hydrogen bond acceptor (A), one hydrogen bond donors (D), one hydrophobic group (H), and one positively charged group (P), ADHP. The hypothesis was further validated for its integrity and significance using enrichment analysis. Subsequently, an atom-based 3D-QSAR model was built using the common pharmacophore hypothesis (CPH). The developed 3D-QSAR model was found to be statistically significant with R2 value of 0.9866 and Q2 value of 0.7629. Further screening was accomplished using three-stage docking process using the Glide algorithm. The resultant lead molecules were examined for its drug-like properties using the Qikprop algorithm. Finally, the calculated pIC50 values of the lead compounds were validated by the AutoQSAR algorithm. Overall, the results from our analysis highlights that lisinopril (DB00722) is predicted to bind better with NA than currently approved drug. In addition, it has the best match in binding geometry conformations with the existing NA inhibitor. Note that the antiviral activity of lisinopril is reported in the literature. However, our paper is the first report on lisinopril activity against influenza A virus infection. These results are envisioned to help design the novel NA inhibitors with an increased antiviral efficacy.

2D-QSAR and 3D-QSAR simulations for the reaction rate constants of organic compounds in ozone-hydrogen peroxide oxidation.

Synergistic oxidation of ozone (O3) and hydrogen peroxide (H2O2) is an effective water treatment for the elimination of organic pollutants. In this study, 23 organic compounds were conducted to study the reaction rate constants during O3-H2O2 oxidation. Then, two- and three-dimensional quantitative structure-activity relationship (QSAR) models were established to investigate the factors influencing the reaction rate constants by using multiple linear regression method and comparative molecular similarity index analysis (CoMSIA) method, respectively. Both of the two models showed good performance on predicting the reaction rate constants, the associated statistical indices of 2D-QSAR and 3D-QSAR models were R2 = 0.898 and 0.952, q2 = 0.841 and 0.951, Qext2 = 0.968 and 0.970, respectively. But varied in the influence factors, as for the 2D-QSAR model, three quantum chemical parameters, included dipole moment, the largest change of charge in each atom during the nucleophilic attack, the maximum positive partial charge on a hydrogen atom linked with a carbon atom affected the reaction rate. While in the 3D-QSAR model, the electrostatic field played the most important role in evaluating the reaction rate with the contribution of 35.8%, followed by hydrogen bond acceptor and hydrophobic fields with the contribution of 24.9% and 23.2%, respectively. These two models provided predictive tools to study the influencing factors for the degradation of organics and might potentially be applied for estimating the removal properties of unknown organics in O3-H2O2 oxidation process.

Deciphering the crucial molecular properties of a series of Benzothiazole Hydrazone inhibitors that targets anti-apoptotic Bcl-xL protein.

The Bcl-2 family proteins are the central regulators of apoptosis. Due to its predominant role in cancer progression, the Bcl-2 family proteins act as attractive therapeutic targets. Recently, molecular series of Benzothiazole Hydrazone (BH) inhibitors that exhibits drug-likeness characteristics, which selectively targets Bcl-xL have been reported. In the present study, docking was used to explore the plausible binding mode of the highly active BH inhibitor with Bcl-xL; and Molecular Dynamics (MD) simulation was applied to investigate the stability of predicted conformation over time. Furthermore, the molecular properties of the series of BH inhibitors were extensively investigated by pharmacophore based 3D-QSAR model. The docking correctly predicted the binding mode of the inhibitor inside the Bcl-xL hydrophobic groove, whereas the MD-based free energy calculation exhibited the binding strength of the complex over the time period. Furthermore, the residue decomposition analysis revealed the major energy contributing residues - F105, L108, L130, N136, and R139 - involved in complex stability. Additionally, a six-featured pharmacophore model - AAADHR.89 - was developed using the series of BH inhibitors that exhibited high survival score. The statistically significant 3D-QSAR model exhibited high correlation co-efficient (R2 = .9666) and cross validation co-efficient (Q2 = .9015) values obtained from PLS regression analysis. The results obtained from the current investigation might provide valuable insights for rational drug design of Bcl-xL inhibitor synthesis.

Design, synthesis and 3D-QSAR studies of novel 1,4-dihydropyridines as TGFß/Smad inhibitors.

Targeting TGFß/Smad signaling is an attractive strategy for several therapeutic applications given its role as a key player in many pathologies, including cancer, autoimmune diseases and fibrosis. The class of b-annelated 1,4-dihydropyridines (DHPs) represents promising novel pharmacological tools as they interfere with this pathway in a novel fashion, i.e. through induction of TGFß receptor type II degradation. In the present work, >40 rationally designed, novel DHPs were synthesized and evaluated for TGFß inhibition, substantially expanding the current understanding of the SAR profile. Key findings include that the 2-position tolerates a wide variety of polar functionalities, suggesting that this region could possibly be solvent-exposed within the (thus far) unknown cellular target. A structural explanation for pathway selectivity is provided based on a diverse series of 4″-substituted DHPs, including molecular electrostatic potential (MEP) calculations. Moreover, the absolute configuration for the chiral 4-position was determined by X-ray crystal analysis and revealed that the bioactive (+)-enantiomers are (R)-configured. Another key objective was to establish a 3D-QSAR model which turned out to be robust (r(2) = 0.93) with a good predictive power (r(2)pred = 0.69). This data further reinforces the hypothesis that this type of DHPs exerts its novel TGFß inhibitory mode of action through binding a distinct target and that unspecific activities that would derive from intrinsic properties of the ligands (e.g., lipophilicity) play a negligible role. Therefore, the present study provides a solid basis for further ligand-based design of additional analogs or DHP scaffold-derived compounds for hit-to-lead optimization, required for more comprehensive pharmacological studies in vivo.