Ligand-based Pharmacophore Model Research Articles

Optimization of virtual screening against phosphoinositide 3-kinase delta: Integration of common feature pharmacophore and multicomplex-based molecular docking

Extensive research has accumulated which suggests that phosphatidylinositol 3-kinase delta (PI3Kδ) is closely related to the occurrence and development of various human diseases, making PI3Kδ a highly promising drug target. However, PI3Kδ exhibits high homology with other members of the PI3K family, which poses significant challenges to the development of PI3Kδ inhibitors. Therefore, in the present study, a hybrid virtual screening (VS) approach based on a ligand-based pharmacophore model and multicomplex-based molecular docking was developed to find novel PI3Kδ inhibitors. 13 crystal structures of the human PI3Kδ-inhibitor complex were collected to establish models. The inhibitors were extracted from the crystal structures to generate the common feature pharmacophore. The crystallographic protein structures were used to construct a naïve Bayesian classification model that integrates molecular docking based on multiple PI3Kδ conformations. Subsequently, three VS protocols involving sequential or parallel molecular docking and pharmacophore approaches were employed. External predictions demonstrated that the protocol combining molecular docking and pharmacophore resulted in a significant improvement in the enrichment of active PI3Kδ inhibitors. Finally, the optimal VS method was utilized for virtual screening against a large chemical database, and some potential hit compounds were identified. We hope that the developed VS strategy will provide valuable guidance for the discovery of novel PI3Kδ inhibitors.

Quinoline-based Schiff bases as possible antidiabetic agents: ligand-based pharmacophore modeling, 3D QSAR, docking, and molecular dynamics simulations study.

α-Glucosidase enzyme inhibition is a legitimate approach to combat type 2 diabetes mellitus as it manages to control postprandial hyperglycemia. In this pursuit, a literature search identified quinoline-based molecules as potential α-glucosidase inhibitors. Thus our intended approach is to identify pharmacophoric features responsible for the α-glucosidase inhibition. This was achieved by performing, ligand-based pharmacophore modeling, 3D QSAR model development, pharmacophore-based screening of a rationally designed quinoline-based benzohydrazide Schiff base library, identifying, synthesizing and characterizing molecules (6a-6j) by IR, (1H and 13C) NMR, and mass studies. Further, these molecules were evaluated for α-glucosidase and α-amylase inhibitory potential. Compound 6c was found to inhibit α-glucosidase enzyme with an IC50 value of 12.95 ± 2.35 μM. Similarly, compound 6b was found to have an IC50 value of 19.37 ± 0.96 μM as compared to acarbose (IC50: 32.63 ± 1.07 μM); the inhibitory kinetics of compounds 6b and 6c revealed a competitive type of inhibition; the inhibitory effect can be attributed to its mapped pharmacophoric feature and model validation with a survival score of 5.0697 and vector score of 0.9552. The QSAR model showed a strong correlation with an R 2 value of 0.96. All the compounds (6a-6j) showed no toxicity in L929 cell lines by the MTT assay method. Further, the binding orientation and stability of the molecules were assessed using molecular docking studies and MD trajectory analysis. The energy profile of the molecules with protein as a complex and molecules alone was evaluated using MM/GBSA and DFT calculations, respectively; finally, the pharmacokinetic profile was computed using ADMET analysis.

Ligand based pharmacophore modelling and integrated computational approaches in the quest for small molecule inhibitors against hCA IX.

Carbonic anhydrase IX is an important biomarker to fight hypoxic tumours in both initial and metastatic stages of many forms of cancer. Overexpression of hCA IX in the hypoxic environment, has an active role in pH maintenance and makes the hCA IX a better target for the inhibitors targeting specific types of cancer stages. Being a member of the carbonic anhydrase family and having sixteen isoforms, it is important to have a selective inhibition of hCA IX to limit the disruption in the biological and metabolic pathways where other isoforms of hCA are localised and to avoid the other toxicity and adverse effects we try to find selective hCA IX inhibitors from a natural derivative. In the process of finding selective hCA inhibitors we developed a pharmacophore model based on existing inhibitors with IC50 values of less than 50 nm, which is then validated with the external decoy set and used for database searching followed by virtual screening to identify the hits based on the pharmacophore fit score and RMSD. Molecular docking studies were performed to identify protein ligand interaction and molecular dynamics simulation studies to analyse the stability of the complex and DFT studies were carried out. The initial screening yielded 43 hits with the RMSD value less than 1, which when subjected to docking exhibited very good interaction with key residues ZN301, HIS94, HIS96 and HIS119. The top 4 compounds in the molecular dynamics simulation studies for 100 ns provided useful insights on the stability of the complex and the DFT studies confirmed the energy variation between HOMO and LUMO is within an acceptable range. An average binding score of -7.8 Kcal mol-1 for the lead compounds and high stability margin in the dynamics study concludes that these lead compounds demonstrated outstanding potential for hCA IX inhibitory action theoretically and that further experimental studies for selective inhibition are inevitable.

Insilico exploration C. koseri ATP synthase inhibitors by pharmacophore-based virtual screening, molecular docking and MD simulation.

Citrobacter koseri is a gram-negative rod that causes infections in people who have significant comorbidities and are immunocompromised. Antibiotic-resistant strains are becoming more common, which complicates infection treatment and highlights the need for innovative, effective drugs to fight these resistant strains. The enzyme complex ATP synthase participates in the adenosine triphosphate (ATP) synthesis, the fundamental energy currency of cells. This study used Computer-Aided Drug Design approaches to identify potential inhibitors of C. koseri ATP synthase. SWISS-MODEL was used to predict the 3D structure of C. koseri ATP synthase. A ligand-based pharmacophore model was developed using chemical features of ampicillin. Following ligand-based virtual screening across nine databases, the 2043 screened hits were docked to the ATP synthase active site using the standard precision mode of the glide tool. Based on their binding affinities, the top ten compounds were selected for additional investigation. The binding affinities of the chosen compounds ranged from -10.021 to -8.452 kcal/mol. The top four compounds (PubChem-25230613, PubChem-74936833, CHEMBL263035, PubChem-44208924) with the best ADMET characteristics and binding modes were chosen. Thus, the feasible binding mechanisms of the selected compounds were subjected to stability analysis using the MD Simulation study, which revealed the compounds' stability as potent inhibitors within the protein binding pocket. This computational approach provides important insights into the rational design of novel therapeutics and emphasizes the importance of targeting essential metabolic pathways when combating antibiotic-resistant pathogens. Future experimental validation and optimization of the identified inhibitors is required to determine their efficacy and safety profiles for clinical use.

Exploration of SAM-I riboswitch inhibitors: In-Silico discovery of ligands to a new target employing multistage CADD approaches

Targeting riboswitches, regulatory elements responsible for the expression of essential genes, is taking central stage in the new era of antibacterial medications discovery due to the emergence of antibiotic resistance. The S-Adenosyl methionine-I (SAM-I) riboswitch works through transcription termination in a negative feedback manner modulated by the natural ligand SAM. SAM-I riboswitch is specific to bacteria and found mainly in gram-positive bacteria such as Bacillus anthracis. Analyzing the interactions of the co-crystallized structure of SAM-I riboswitch aptamer with its native ligand SAM clarified the needed chemical structural features to achieve binding. Acknowledging those features, structure-based and ligand-based pharmacophore models were built for filtration use in screening the OTAVA Chemical library and the Pubchem database. For further filtration enhancement, the physicochemical properties of SAM were used as a second filtration criterion. Compounds obtained as output from previous steps were energy minimized, and the lowest energy conformer structures were docked to SAM-I using MOE, v.2019.01. S-score and ligand interactions were used to assess the best hits. This yielded eight promising compounds to which molecular dynamics (MD) simulations with SAM-I aptamer were applied using GROMACS 2020.3 package affirming stable binding interactions and binding energetics similar to SAM. Moreover, pharmacokinetic and drug-like properties of those eight hits were assessed using SWISS-ADME. According to the combined computational methods and PK/Tox assessment, compound 20 was the most promising and thus can be considered a lead for future evaluation and optimization as a candidate new antibacterial agent targeting a new biomolecule eliciting a new mechanism of action.

Discovery of Potential Inhibitors for SFRP3: Ligand-Based 3D Pharmacophore, Virtual Screening, Molecular Docking, and Dynamics Studies

Cancer is a complicated and diverse family of diseases characterized by the body’s aberrant cells growing and spreading out of control. It is one of the major causes of mortality in the world and may affect almost every organ or tissue in the body. One of the most prevalent forms of malignant tumors that affect both men and women is bone cancer. The study introduces the soluble frizzled-related protein SFRP3 as a significant participant. It functions as a tumor suppressor and regulator as well as an antagonist of the Wnt signaling pathway. It interacts directly with Wnts, regulating Wnt signaling and directing cell proliferation and differentiation in certain cell types. The study focuses on SFRP3 as a possible target for bone cancer therapy. The purpose is to find prospective medication candidates. Several databases are listed as possible drug compound sources, including NCI_Natural Products, Enamine, and specifications. Potent drugs from the selected databases are scrutinized and identified using ligand-based pharmacophore modeling. The binding affinity and interactions between the selected compounds and the SFRP3-modeled protein are evaluated using virtual screening and molecular docking approaches. The selection of lead compounds is based on their scores, binding affinity, and interactions, which indicate their potential as therapeutic candidates. To ensure that the contacts stay stable throughout time, molecular dynamics modeling is used to analyze the stability of the Protein-Ligand complex. The investigation leads to the identification of the top three compounds from each of the three databases that show potential against the target protein, SFRP3.

Ligand-based pharmacophore modelling, structure optimisation, and biological evaluation for the identification of 2-heteroarylthio-N-arylacetamides as novel HSP90 C-terminal inhibitors

Targeting Heat shock protein 90 (HSP90) C-terminus is an important strategy to develop HSP90 inhibitors without inducing heat shock response. The development of C-terminal inhibitors, however, is hampered by a lack of understanding regarding the interaction between the HSP90 C-terminus and the present inhibitors. We collected seven classical and structurally diverse HSP90 C-terminal inhibitors and constructed a ligand-based pharmacophore model. The subsequent virtual screening and structural optimisation led to the identification of 2-heteroarylthio-N-arylacetamides as novel HSP90 C-terminal inhibitors. 9 and 27 exhibited strong antitumour activity in vitro by inhibiting proliferation and inducing apoptosis in multiple cancer cell lines. These compounds disrupted the interaction between HSP90 C-terminus and peptidylprolyl isomerase D, exerting a stronger inhibitory effect than novobiocin. 27 significantly induced the degradation of HSP90 clients without triggering heat shock response. In an in vivo study using 4T1 mice breast cancer models, 9 showed a potent antitumour effect without obvious toxicity.

Identification of Dual-Target Inhibitors for Epidermal Growth Factor Receptor and AKT: Virtual Screening Based on Structure and Molecular Dynamics Study.

Epidermal growth factor EGFR is an important target for non-small cell lung (NSCL) cancer, and inhibitors of the AKT protein have been used in many cancer treatments, including those for NSCL cancer. Therefore, searching small molecular inhibitors which can target both EGFR and AKT may help cancer treatment. In this study, we applied a ligand-based pharmacophore model, molecular docking, and MD simulation methods to search for potential inhibitors of EGFR and then studied dual-target inhibitors of EGFR and AKT by screening the immune-oncology Chinese medicine (TCMIO) database and the human endogenous database (HMDB). It was found that TCMIO89212, TCMIO90156, and TCMIO98874 had large binding free energies with EGFR and AKT, and HMDB0012243 also has the ability to bind to EGFR and AKT. These results may provide valuable information for further experimental study.

Virtual screening approach for the discovery of selective 5α-reductase type II inhibitors for benign prostatic hyperplasia treatment.

Background: 5α-Reductase type II (5αR2) inhibition is a promising strategy for benign prostatic hyperplasia treatment. A computational approach including virtual screening, ligand-based 3Dpharmacophore modeling, 2D quantitative structure-activity relationship and molecular docking simulations were adopted to develop novel inhibitors. Results: Hits were first filtered via the validated pharmacophore and 2D quantitative structure-activity relationship models. Docking on the recently determined cocrystallized structure of 5αR2 showed three promising hits. Visual inspection results were compared with finasteride ligand and dihydrotestosterone as reference, to explain the role of binding to Glu57 and Tyr91 for 5αR2 selective inhibition. Conclusion: Alignment between Hit 2 and finasteride in the binding pocket showed similar binding modes. The biological activity prediction showed antitumor and androgen targeting activity of the new hits.

Theoretical investigation on known renin inhibitors and generation of ligand-based pharmacophore models for hypertension treatment

The renin enzyme is considered a promising target for hypertension and renal diseases. Over the last three decades, several experimental and theoretical studies have been engaged in the discovery of potent renin inhibitors. The identified inhibitors that undergo clinical trials are still failing to meet the criteria of potency and safety. To date, there is no specific FDA-approved drug for renin inhibition. Our theoretical opinion describes that the most potent compounds identified in experimental studies but lacking safety and overdose issues could be solved by finding similar molecules that are stable, very active, and have no side effects, which will kick start the drug discovery process. Here, we utilized the most potent direct renin inhibitors reported earlier, followed further by our theoretical study reported in 2019. Ligand-based virtual screening, density functional theory, and dynamic simulation studies were employed to explore the identified compounds and co-crystallized molecule in the protein structure. From the diverse databases, we have identified several identical molecules based on their structural features, such as functional groups like hydrophobic (H), aromatic rings (R), hydrogen bond acceptor (A), and donor (D). The HHHPR five-point pharmacophore feature was identified as a template pharmacophore to search the potential compounds from the Enamine and LifeChemical databases and have a good fitness score with known renin inhibitors. Furthermore, theoretical validation was done through several studies that confirmed the activity of the identified molecules. Overall, we propose that these compounds might break the failure in adverse events and improve the potency of hypertension treatment. Communicated by Ramaswamy H. Sarma

Identification of novel small molecule inhibitors for solute carrier SGLT1; a computational exploration

Diabetes results in substantial disabilities, diminished quality of life, and mortality that imposes a huge economic burden on societies and governments worldwide. Despite the absence of specific oral therapies at present, there exists an urgent requirement to develop a novel drug for the treatment of diabetes mellitus. The membrane protein sodium glucose co-transporters (SGLT1) present a captivating therapeutic target for diabetes, given its pivotal role in facilitating glucose absorption in the small intestine, offering immense promise for potential therapeutic intervention. In this connection, the present study is aimed at identifying potential inhibitors of SGLT1 from a small molecule database, including compounds from both natural as well as synthetic origins. A comprehensive approach was employed, by integrating homology modeling, ligand-based pharmacophore modeling, virtual screening, and molecular docking simulation. The process resulted in the identification of 16 new compounds, featuring similar attributes as observed for the documented actives. In a systematic screening procedure, five potential virtual hits were selected for simulation studies followed by subsequent binding free energy calculations, providing deeper insight into the time-dependent behavior of protein-ligand complexes in a dynamic state. In conclusion, our findings demonstrated that the identified compounds, particularly compounds 81 and 91, exhibit enhanced stability and favorable binding affinities with the target protein, marking them promising candidates for further investigations. Communicated by Ramaswamy H. Sarma

Identification of novel dual acting ligands targeting the adenosine A2A and serotonin 5-HT1A receptors

GPCRs are a family of transmembrane receptors that are profoundly linked to various neurological disorders, among which is Parkinson’s disease (PD). PD is the second most ubiquitous neurological disorder after Alzheimer’s disease, characterized by the depletion of dopamine in the central nervous system due to the impairment of dopaminergic neurons, leading to involuntary movements or dyskinesia. The current standard of care for PD is Levodopa, a dopamine precursor, yet the chronic use of this agent can exacerbate motor symptoms. Recent studies have investigated the effects of combining A2AR antagonist and 5-HT1A agonist on dyskinesia and motor complications in animal models of PD. It has been proved that the drug combination has significantly improved involuntary movements while maintaining motor activity, highlighting as a result new lines of therapy for PD treatments, through the regulation of both receptors. Using a combination of ligand-based pharmacophore modelling, virtual screening, and molecular dynamics simulation, this study intends on identifying potential dual-target compounds from IBScreen. Results showed that the selected models displayed good enrichment metrics with a near perfect receiver operator characteristic (ROC) and Area under the accumulation curve (AUAC) values, signifying that the models are both specific and sensitive. Molecular docking and ADMET analysis revealed that STOCK2N-00171 could be potentially active against A2AR and 5-HT1A. Post-MD analysis confirmed that the ligand exhibits a stable behavior throughout the simulation while maintaining crucial interactions. These results imply that STOCK2N-00171 can serve as a blueprint for the design of novel and effective dual-acting ligands targeting A2AR and 5-HT1A. Communicated by Ramaswamy H. Sarma

Identification of novel curcumin derivatives against pancreatic cancer: a comprehensive approach integrating 3D-QSAR pharmacophore modeling, virtual screening, and molecular dynamics simulations

Pancreatic cancer, known as the “silent killer,” poses a daunting challenge in cancer therapy. The dysregulation of the PI3Kα signaling pathway in pancreatic cancer has attracted considerable interest as a promising target for therapeutic intervention. In this regard, the use of curcumin derivatives as inhibitors of PI3Kα has emerged, providing a novel and promising avenue for developing effective treatments for this devastating disease. Computational approaches were employed to explore this potential and investigate 58 curcumin derivatives with cytotoxic activity against the Panc-1 cell line. Our approach involved ligand-based pharmacophore modeling and atom-based 3D-QSAR analysis. The resulting QSAR model derived from the best-fitted pharmacophore hypothesis (AAHRR_1) demonstrated remarkable performance with high correlation coefficients (R2) of 0.990 for the training set and 0.977 for the test set. The cross-validation coefficient (Q2) of 0.971 also validated the model’s predictive power. Tropsha’s recommended criteria, including the Y-randomization test, were employed to ensure its reliability. Furthermore, an enrichment study was conducted to evaluate the model’s performance in identifying active compounds. AAHRR_1 was used to screen a curated PubChem database of curcumin-related compounds. Two molecules (CID156189304 and CID154728220) exhibited promising pharmacokinetic properties and higher docking scores than Alpelisib, warranting further investigation. Extensive molecular dynamics simulations provided crucial insights into the conformational dynamics within the binding site, validating their stability and behavior. These findings contribute to our understanding of the potential therapeutic effectiveness of these compounds as PI3Kα inhibitors in pancreatic cancer. Communicated by Ramaswamy H. Sarma

Some New 1,2,4-triazole Derivatives Bearing the Pyrimidine Moiety as Potential Antimycobacterial Agents: Synthesis and Docking Analysis

Background: Pyrimidine and 1,2,4-triazole heterocycles have been linked to a variety of biological and pharmacological properties such as effective bactericides, fungicides, vermicides, insecticides, anticancer and antiviral agents. Accordingly, the synthetic derivatives and analogs of these molecules have attracted attention as potential pharmacological agents. Objective: A novel set of heterocyclic derivatives comprising 1,2,4-triazole, pyrimidine moieties was developed, synthesized, and assessed for their antimicrobial activity. Methods: In this study, we performed ligand-based pharmacophore modeling as a promising design strategy for the design of substituted triazolyl-pyrimidine derivatives as antitubercular agents. The designed compounds were synthesized and characterized by proton, carbon nuclear magnetic resonance spectroscopy, infrared, and mass spectroscopy. Synthesized compounds were screened for anti-TB activity using the agar micro dilution method against M. tuberculosis H37Rv strain. Results: Our results revealed that the target 1,2,4-triazoles 7d, 7e, 7c have potent potency against Gram- (+ve) bacteria S. epidermidis (MICs: 1.7, 3.7, 16.4 μg/mL), whereas final pyrimidines 7c, 7e, 7f, have the strongest antibacterial activity against Gram-(-ve) strain P. aeruginosa (MICs: 3.5, 6.4, 8.4 μg/mL). Among all tested compounds, 7a, 7e, and 7h revealed an outstanding antitubercular activity against M. tuberculosis H37RV strain with MICs of 3.24, 8.93, and 4.70 μg/mL, respectively. The most active ligand 7b reveals highest hydrophobic binding modes with ThrA:127 [2.194 A°], LysA:103 [3.103, 2.164 A°], GlyA:102 [1.713 A°], ArgA:238 [1.713 A°], ValA:101 [2.113 A°] (hydrogen bondings), AspA:129, GluA:201 [Pi-anion], AlaA:246, LeuA:180 [Pi-alkyl] and HisA:179 [3.104 A°] [Pi-Pi], respectively. Conclusion: In this communication, our aim has been verified by the synthesis of 3-methoxy-10,12- dimethyl-8-phenyl-6,7,8,12-tetrahydrobenzo[2,3]oxepino[4,5-d][1,2,4]triazolo[4,3-a] pyrimidine derivatives 7 in which 1,2,4-triazole and pyrimidine moieties with benzoxepine in a single molecular framework were found. After all the above findings, it can be concluded that these molecules become lead molecules for further synthetic and biological evaluation.

A Computational Study on the Structural Prediction of InhA Inhibitors as Antimycobacterial Agents

InhA is an enoyl acyl carrier reductase that catalyzes the chemo-selective reduction of its 2-trans-enoyl-ACP substrate. The pharmacological effects of the frontline medications used in the treatment of tuberculosis are elicited by inhibiting the enzyme InhA, which disrupts the mycolic acid biosynthesis pathway. The present study involves development of ligand-based pharmacophore model, docking studies, generation of 3D-QSAR model, and molecular dynamic simulation studies of virtually screened putative InhA inhibitors. The best field-based 3D-QSAR model was validated using partial least-square regression (PLS) method with high regression coefficient for training set (R 2) = 0.9256 and test set (R 2) = 0.7542, cross-validated coefficient (r cv 2) = 0.72 and R 2 pred = 0.9764. Also, virtual screening yielded compounds 4, 25, 1, and 30 exhibiting appreciable interactions (docking scores −5.972, −3.819, −3.801, and −3.701, respectively with InhA synthetase; PDB ID: 1BVR). Further, ADMET studies supported drug-like potential of compounds 25, 1, and 30 whereas compound 4 showed negligible human oral absorption. The molecular dynamic simulation studies of the top scored molecule 25 suggested stability of 25-1BVR complex over the course of simulation run. Therefore, this work can be helpful for future discovery of novel InhA inhibitors against drug-resistant tuberculosis.

Identification of novel metallo-β-lactamases inhibitors using ligand-based pharmacophore modelling and structure-based virtual screening

Metallo-β-lactamases (MBLs) are a group of enzymes that hydrolyze the most commonly used β-lactam-based antibiotics, leading to the development of multi-drug resistance. The three main clinically relevant groups of these enzymes are IMP, VIM, and NDM. This study aims to introduce potent novel overlapped candidates from a ZINC database retrieved from the 200,583-member natural library against the active sites of IMP-1, VIM-2, and NDM-1 through a straightforward computational workflow using virtual screening approaches. The screening pipeline started by assessing Lipinski’s rule of five (RO5), drug-likeness, and pan-assay interference compounds (PAINS) which were used to generate a pharmacophore model using D-captopril as a standard inhibitor. The process was followed by the consensus docking protocol and molecular dynamic (MD) simulation combined with the molecular mechanics Poisson-Boltzmann Surface Area (MM-PBSA) method to compute the total binding free energy and evaluate the binding characteristics. The absorption, distribution, metabolism, elimination, and toxicity (ADMET) profiles of the compounds were also analyzed, and the search space decreased to the final two inhibitory candidates for B1 subclass MBLs, which fulfilled all criteria for further experimental evaluation. Communicated by Ramaswamy H. Sarma

Insight into the role of phytoalexin naringenin and phytohormone abscisic acid in defense against phytopathogens Phytophthora infestans and Magnaporthe oryzae: In vitro and in silico approaches

Phytoalexin naringenin and phytohormone abscisic acid (ABA) play crucial roles in plant defense and physiology. This work encompassed both experimental and computational approaches to assess their antifungal efficacy against Phytophthora infestans and Magnaporthe oryzae. Naringenin and ABA, isolated from Desmodium sequax, exhibited significant in vitro antifungal activity against both pathogens. Naringenin was moderately active against M. oryzae in a dose-dependent manner, while ABA was not. The antifungal efficacy of ABA against P. infestans (IC50 = 19.7 μg/mL and IC90 = 72.0 μg/mL) was more potent when compared with that of naringenin (IC50 = 53.7 μg/mL and IC90 = 129.2 μg/mL). Computational models provided insights into their interactions with pathogenic enzymes. Naringenin emerged as a novel inhibitor of M. oryzae enzymes (1,3,8-trihydroxynaphthalene reductase and scytalone dehydratase); and together with ABA, it exhibited robust interactions with targeted P. infestans enzymes (chitin synthase and calmodulin). Ligand-based pharmacophore models were constructed for prospective P. infestans inhibitors. These findings highlight the mechanism and antifungal potential of naringenin and ABA and suggest their use as natural fungicides in sustainable agriculture.

In-silicoidentification of small molecule benzofuran-1,2,3-triazole hybrids as potential inhibitors targeting EGFR in lung cancer via ligand-based pharmacophore modeling and molecular docking studies.

The online version contains supplementary material available at 10.1007/s40203-023-00157-1.

Pharmacophore based virtual screening for identification of effective inhibitors to combat HPV 16 E6 driven cervical cancer

Targeting HPV16 E6 has emerged as an effective drug target for the treatment/management of cervical cancer. We utilized pharmacophore-based virtual screening, molecular docking, absorption, distribution, metabolism and excretion (ADME) prediction, and molecular dynamics simulation approach for identifying potential inhibitors of HPV16 E6. Initially, we generated a ligand-based pharmacophore model based on the features of four known HPV16 E6 inhibitors (CA24, CA25, CA26, and CA27) via the PHASE module implanted in the Schrödinger suite. We constructed four-point pharmacophore features viz., three hydrogen bond acceptors (A) and one aromatic ring (R). The common pharmacophore feature further employed as a query for virtual screening against the ASINEX database via Schrödinger suite. The pharmacophore-based virtual screening filtered out top 2000 hits, based on the fitness score. We then applied the high throughput virtual screening (HTVS), standard precision (SP) and extra precision (XP). 1000 compounds were obtained from HTVS docking. Based on the glide score, they were further filtered to 500 hits by employing docking in standard precision mode. Finally, the best four hits and a negative molecule were identified using docking in XP mode. The four lead compounds and a negative molecule were then further subjected to ADME profile prediction by engaging Qikprop module. The ADME properties of the four lead molecules indicate good pharmacokinetic (PK) properties rather than the negative molecule. The binding stability of the HPV16 E6-hit complexes were investigated at a different time scale (100 ns) by using the desmond package and the results were examined using Root Mean Square Deviation (RMSD) and Root Mean Square Fluctuation (RMSF) and it revealed the stability of the protein-ligand complex throughout the simulation. Key residues, CYS 51 and GLN 107, also play a crucial role in enhancing the stability of the protein-ligand complex during the simulation. Furthermore, the binding free energy of the HPV16 E6-leads complexes was analyzed by prime which revealed that the ΔGbind coulomb and ΔGbind vdW interactions are crucially contributes to the binding affinity. In order to validate the computational findings, the efficacy of benzoimidazole and benzotriazole were ascertained for regulating ME180 cervical cancer cell survival, migration and ability to release MMP-2.

Structure-guided Design and Optimization of small Molecules as Pancreatic Lipase Inhibitors using Pharmacophore, 3D-QSAR, Molecular Docking, and Molecular Dynamics Simulation Studies.

Obesity has now become a global issue due to the increase in the population of obese people. It also substantially impacts the individual's social, financial, and psychological well-being, which may contribute to depression. Being overweight induces many metabolic and chronic disorders, urging many researchers to focus on developing the drug for obesity treatment. Pancreatic lipase inhibitors and natural product/compound-derived pancreatic lipase inhibitors have recently received much attention because of their structural variety and low toxicity. This study aimed to build pharmacophores and QSAR for analyzing the necessary structure of pancreatic lipase inhibitors and designing new molecules with the best activity. Ligand-based pharmacophore modeling and Atom-Based 3D-QSAR were carried out using the PHASE module of Schrodinger to determine the critical structural properties necessary for pancreatic lipase (PL) inhibitory activity. A total of 157 phytoconstituents and a standard drug, orlistat, were selected for the present study. Considering the important features for pancreatic lipase inhibition, 15 new molecules were designed and subjected to molecular docking studies and molecular dynamics simulations. The activity of designed molecules was predicted using the Atom- Based QSAR tool of the PHASE module. The top docked score molecule is structure-7 with a docking score of -6.094 Kcal/mol, whereas the docking score of orlistat and tristin is -3.80Kcal/mol and -5.63Kcal/mol, respectively. The designed molecules have a high docking score and good stability, are in the desirable ADME range and are derived from natural products, so they might be used as lead molecules for anti-obesity drug development.