Silico Screening Research Articles

In Silico Screening and Molecular Dynamics Simulations against Tyrosine-protein Kinase Fyn Reveal Potential Novel Therapeutic Candidates for Bovine Papillomatosis.

Decreased beef productivity due to papillomatosis has led to the development and identification of novel targets and molecules to treat the disease. Protein kinases are promising targets for the design of numerous chemotherapy drugs. This study aimed to screen and design new inhibitors of bovine Fyn, a protein kinase, using structure-based computational methods, such as molecular docking and molecular dynamics simulation (MDS). To carry out the molecular docking analysis, five ligands obtained through structural similarity between active compounds along with the cross-inhibition function between the ChEMBL and Drugbank databases were used. Molecular modeling was performed, and the generated models were validated using PROCHECK and Verify 3D. Molecular docking was performed using Autodock Vina. The complexes formed between Fyn and the three best ligands had their stability assessed by MDS. In these simulations, the complexes were stabilized for 100 ns in relation to a pressure of 1 atm, with an average temperature of 300 k and a potential energy of 1,145,336 kJ/m converged in 997 steps. Docking analyses showed that all selected ligands had a high binding affinity with Fyn and presented hydrogen bonds at important active sites. MDS results support the docking results, as the ligand showed similar and stable interactions with amino acids present at the binding site of the protein. In all simulations, sorafenib obtained the best results of interaction with the bovine Fyn. The results highlight the identification of possible bovine Fyn inhibitors; however, further studies are important to confirm these results experimentally.

In Silico Screening of 1,3,4-Thiadiazole Derivatives as Inhibitors of Vascular Endothelial Growth Factor Receptor-2 (VEGFR-2).

Angiogenesis plays a pivotal role in the growth, survival, and metastasis of solid tumors, with Vascular Endothelial Growth Factor Receptor-2 (VEGFR-2) being overexpressed in many human solid tumors, making it an appealing target for anti-cancer therapies. This study aimed to identify potential lead compounds with azole moiety exhibiting VEGFR-2 inhibitory effects. A ligand-based pharmacophore model was constructed using the X-ray crystallographic structure of VEGFR-2 complexed with tivozanib (PDB ID: 4ASE) to screen the ZINC15 database. Following virtual screening, six compounds demonstrated promising docking scores and drug-likeness comparable to tivozanib. These hits underwent detailed pharmacokinetic analysis to assess their absorption, distribution, metabolism, excretion, and toxicity (ADMET) properties. Furthermore, Density Functional Theory (DFT) analysis was employed to investigate the molecular orbital properties of the top hits from molecular docking. Molecular dynamics (MD) simulations were conducted to evaluate the conformational stability of the complexes over a 100 ns run. Results indicated that the compounds (ZINC8914312, ZINC8739578, ZINC8927502, and ZINC17138581) exhibited the most promising lead requirements for inhibiting VEGFR-2 and suppressing angiogenesis in cancer therapy. This integrated approach, combining pharmacophore modeling, molecular docking, ADMET studies, DFT analysis, and MD simulations, provides valuable insights into the identification of potential anti-cancer agents targeting VEGFR-2.

In Silico Screening of FDA‐Approved Anthelmintic Drugs Against LuxR Protein as Quorum‐Sensing Inhibitors and Exploration of Their Binding Mechanism and Electronics Properties

AbstractTreating bacterial infections triggered by multidrug‐resistant bacteria is a global priority. Issue of multidrug resistance can be managed by inhibiting bacterial quorum sensing mechanism. Quorum‐sensing inhibitors (QSIs) are promising alternatives to antibiotics. Herein, a library of FDA‐approved anthelmintic medications was screened using in silico techniques for LuxR protein associated with the quorum‐sensing (QS) mechanism of Staphylococcus aureus. Drug repurposing can reduce the time and financial risk of drug development. Seven FDA‐approved drugs (Fenbendazole, Mebendazole, Flubendazole, Praziquantel, Oxyclozanide, Rafoxanide, and Albendazole) showed strong binding affinity to the LuxR protein with binding free energy less than −6.00 kcal/mol. Molecular dynamic simulation (100 ns) of the docked complexes revealed that Fenbendazole and Rafoxanide remain at the binding pocket of the LuxR protein most of the time. During the whole simulation period, backbone of all seven complexes displayed small fluctuation in the RMSD and Rg. The free energy landscape of LuxR–Rafoxanide and LuxR–Fenbendazole complexes showed promising stability compared to the rest of the complexes. Both the complexes showed excellent MMPBSA binding free energy: −92.882 ± 15.636 kJ/mol (LuxR–Rafoxanide) and −74.873 ± 9.233 kJ/mol (LuxR–Fenbendazole). The reactivity of the ligands was ascertained from their DFT‐based various descriptors.

In Vitro In Silico Screening Strategy and Mechanism of Novel Tyrosinase Inhibitory Peptides from Nacre of Hyriopsis cumingii.

For thousands of years, pearl and nacre powders have been important traditional Chinese medicines known for their skin whitening effects. To prepare the enzymatic hydrolysates of Hyriopsis cumingii nacre powder (NP-HCH), complex enzymatic hydrolysis by pineapple protease and of neutral protease was carried out after the powder was pre-treated with a high-temperature and high-pressure method. The peptides were identified using LC-MS/MS and picked out through molecular docking and molecular dynamics simulations. Subsequently, the tyrosinase inhibitory and antioxidant properties of novel tyrosinase inhibitory peptides were investigated in vitro. In addition, the enzymatic activity of tyrosinase in B16F10 cells as well as melanin content and antioxidant enzyme levels were also examined. The results showed that a tyosinase inhibitory peptide (Tyr-Pro-Asn-Pro-Tyr, YPNPY) with an efficient IC50 value of 0.545 ± 0.028 mM was identified. The in vitro interaction results showed that YPNPY is a reversible competitive inhibitor of tyrosinase, suggesting that it binds to the free enzyme. The B16F10 cell whitening test revealed that YPNPY can reduce the melanin content of B16F10 cells by directly inhibiting the activity of intracellular tyrosinase. Additionally, it indirectly affects melanin production by acting as an antioxidant. These results suggest that YPNPY could be widely used as a tyrosinase inhibitor in whitening foods and drugs.

In Silico Screening, Molecular Dynamics Simulation and Binding Free Energy Identify Single-Point Mutations That Destabilize p53 and Reduce Binding to DNA.

Considering p53's pivotal role as a tumor suppressor protein, proactive identification and characterization of potentially harmful p53 mutations are crucial before they appear in the population. To address this, four computational prediction tools-SIFT, Polyphen-2, PhD-SNP, and MutPred2-utilizing sequence-based and machine-learning algorithms, were employed to identify potentially deleterious p53 nsSNPs (nonsynonymous single nucleotide polymorphisms) that may impact p53 structure, dynamics, and binding with DNA. These computational methods identified three variants, namely, C141Y, C238S, and L265P, as detrimental to p53 stability. Furthermore, molecular dynamics (MD) simulations revealed that all three variants exhibited heightened structural flexibility compared to the native protein, especially the C141Y and L265P mutations. Consequently, due to the altered structure of mutant p53, the DNA-binding affinity of all three variants decreased by approximately 1.8 to 9.7 times compared to wild-type p53 binding with DNA (14 μM). Notably, the L265P mutation exhibited an approximately ten-fold greater reduction in binding affinity. Consequently, the presence of the L265P mutation in p53 could pose a substantial risk to humans. Given that p53 regulates abnormal tumor growth, this research carries significant implications for surveillance efforts and the development of anticancer therapies.

Cnicus benedictus: Folk Medicinal Uses, Biological Activities, and In Silico Screening of Main Phytochemical Constituents.

Traditional medicine has long recognized the therapeutic potential of Cnicus benedictus, and recent scientific research has shed light on the pharmacological properties of this plant. The bioactive compounds that can be extracted from it, such as the sesquiterpene lactones arctigenin, arctiin, and cnicin, are very interesting to researchers.In this article, based on available data from pre-clinical in vitro and in vivo studies, we delve into the pharmacology of the active constituents of this plant to explore its potential therapeutic applications and underlying mechanisms of action. In addition, we present a computer analysis designed to reveal the pharmacokinetic and toxicological properties of the main phytochemicals that are active in C. benedictus through new in silico techniques and predictive tools such as SwissADME and PubChem.The data from the in silico study presented here support the traditional use of C. benedictus, as well as its promise as a source of new therapeutic chemical compounds.

Assessment of Antifungal Potentials of Ethanol Extract of Cleistocalyx operculatus Roxb Against Cercospora nicotianae for Pesticidal Applicability: In Vitro and In Silico Screening

Assessment of Antifungal Potentials of Ethanol Extract of Cleistocalyx operculatus Roxb Against Cercospora nicotianae for Pesticidal Applicability: In Vitro and In Silico Screening

In Silico Screening of Sulfonamide Derivatives against Glycolytic Enzymes Reveals Mutation‐Independent Interactions of Sulfisoxazole and Sulfamethazine

AbstractGlycolysis is a highly conserved biochemical process that involves the sequential conversion of glucose to pyruvate and the generation of adenosine triphosphate (ATP), generating energy for cellular functions. This is carried out by several enzymes that play an important role in glucose metabolism. The sulfonamide group of drugs is commonly used as an antibiotic that inhibits the bacterial folic acid production pathway, although its effects on glycolytic enzymes are unclear. Since altered glycolytic enzyme expression is linked to a variety of metabolic disorders as well as cancer, the quest for new ligands against glycolytic enzymes is never over. We revealed that different sulfonamide derivatives interact with glycolytic enzymes with varying binding affinities. Among the selected sulfonamides, sulfisoxazole and sulfamethazine had greater binding scores to certain glycolytic enzymes than others. In silico point mutation analysis predicts that sulfisoxazole and sulfamethazine interact with certain glycolytic enzymes in a residue‐independent manner. This research generates a repository of the 2D interactions of sulfonamide derivatives with glycolytic enzymes, binding energies, impacts of induced point mutations on the local environment, and changes in protein structural flexibility. In the future, sulfisoxazole and sulfamethazine may be repurposed as specific glycolytic enzyme inhibitors to combat a variety of glycolysis‐related metabolic disorders.

In Silico Screening of Therapeutic Targets as a Tool to Optimize the Development of Drugs and Nutraceuticals in the Treatment of Diabetes mellitus: A Systematic Review.

The Target-Based Virtual Screening approach is widely employed in drug development, with docking or molecular dynamics techniques commonly utilized for this purpose. This systematic review (SR) aimed to identify in silico therapeutic targets for treating Diabetes mellitus (DM) and answer the question: What therapeutic targets have been used in in silico analyses for the treatment of DM? The SR was developed following the guidelines of the Preferred Reporting Items Checklist for Systematic Review and Meta-Analysis, in accordance with the protocol registered in PROSPERO (CRD42022353808). Studies that met the PECo strategy (Problem, Exposure, Context) were included using the following databases: Medline (PubMed), Web of Science, Scopus, Embase, ScienceDirect, and Virtual Health Library. A total of 20 articles were included, which not only identified therapeutic targets in silico but also conducted in vivo analyses to validate the obtained results. The therapeutic targets most frequently indicated in in silico studies were GLUT4, DPP-IV, and PPARγ. In conclusion, a diversity of targets for the treatment of DM was verified through both in silico and in vivo reassessment. This contributes to the discovery of potential new allies for the treatment of DM.

In Silico Screening of Phytocompounds from West African Traditional Medicine and Molecular Docking Targeting Dengue Virus Protein NS2B/NS3.

Traditional medicine offers a wide range of application for in silico study techniques. This drug research and development strategy is embryonic in the West African context, particularly in Burkina Faso, which is increasingly faced with emerging diseases such as dengue fever. Circulation of the 4 serotypes of this virus has been documented in the country. This study aims to evaluate the therapeutic potential of phytocompounds contained in the West African pharmacopoeia against dengue virus NS2B/NS3 protein, using computational methods integrating several software packages and databases. Based on a literature review, we identified 191 molecules from 30 plants known for their antiviral effects. Five met the inclusion criteria for molecular docking: patulin from calotropis procera, resiniferonol from Euphorbia poissonii, Securinol A from Flueggea virosa, Shikimic acid and Methyl gallate from Terminalia macroptera. The best binding scores were observed between resiniferonol and the serotypes 1, 2 and 4 NS2B/NS3 protease, with binding energies of -7.4 Kcal/mol, -6.8 Kcal/mol and -7.3 Kcal/mol respectively; while the NS2B/NS3 protease of serotype 3 had the best affinity for securinol A (-7 Kcal/mol). This study points the way to further research in computer aided drug design field and calls for multidisciplinary collaboration to promote West African medicinal plants against health challenges.

Searching for Novel HDAC6/Hsp90 Dual Inhibitors with Anti-Prostate Cancer Activity: In Silico Screening and In Vitro Evaluation.

Prostate cancer (PCA) is one of the most prevalent types of male cancers. While current treatments for early-stage PCA are available, their efficacy is limited in advanced PCA, mainly due to drug resistance or low efficacy. In this context, novel valuable therapeutic opportunities may arise from the combined inhibition of histone deacetylase 6 (HDAC6) and heat shock protein 90 (Hsp90). These targets are mutually involved in the regulation of several processes in cancer cells, and their inhibition is demonstrated to provide synergistic effects against PCA. On these premises, we performed an extensive in silico virtual screening campaign on commercial compounds in search of dual inhibitors of HDAC6 and Hsp90. In vitro tests against recombinant enzymes and PCA cells with different levels of aggressiveness allowed the identification of a subset of compounds with inhibitory activity against HDAC6 and antiproliferative effects towards LNCaP and PC-3 cells. None of the candidates showed appreciable Hsp90 inhibition. However, the discovered compounds have low molecular weight and a chemical structure similar to that of potent Hsp90 blockers. This provides an opportunity for structural and medicinal chemistry optimization in order to obtain HDAC6/Hsp90 dual modulators with antiproliferative effects against prostate cancer. These findings were discussed in detail in the study.

In Silico Screening Identification of Fatty Acids and Fatty Acid Derivatives with Antiseizure Activity: In Vitro and In Vivo Validation.

High fat diets have been used as complementary treatments for seizure disorders for more than a century. Moreover, many fatty acids and derivatives, including the broad-spectrum antiseizure medication valproic acid, have been explored and used as pharmacological agents to treat epilepsy. In this work, we have explored the anticonvulsant potential of a large library of fatty acids and fatty acid derivatives, the LIPID MAPS Structure Database, using structure-based virtual screening to assess their ability to block the voltage-gated sodium channel 1.2 (NaV1.2), a validated target for antiseizure medications. Four of the resulting in silico hits were submitted for experimental confirmation using in vitro patch clamp experiments, and their protective role was evaluated in an acute mice seizure model, the Maximal Electroshock seizure model. These four compounds were found to protect mice against seizures. Two of them exhibited blocking effects on NaV1.2, CaV2.2, and CaV3.1.

Uncertainty management for In Silico screening of reversed-phase liquid chromatography methods for small compounds

The process of developing new reversed-phase liquid chromatography methods can be both time-consuming and challenging. To meet this challenge, statistics-based strategies have emerged as cost-effective, efficient and flexible solutions. In the present study, we use a Bayesian response surface methodology, which takes advantage of the knowledge of the pKa values of the compounds present in the analyzed sample to model their retention behavior. A multi-criteria decision analysis (MCDA) was then developed to exploit the uncertainty information inherent in the model distributions. This strategic approach is designed to integrate seamlessly with quantitative structure retention relationship (QSRR) models, forming an initial in-silico screening phase. Of the two methods presented for MCDA, one showed promising results. The method development process was carried out with the optimization phase, generating a design space that corroborates the results of the selection phase.

Identification of Anticancer Peptides from the Genome of Candida albicans: in Silico Screening, in Vitro and in Vivo Validations.

Anticancer peptides (ACPs) are promising future therapeutics, but their experimental discovery remains time-consuming and costly. To accelerate the discovery process, we propose a computational screening workflow to identify, filter, and prioritize peptide sequences based on predicted class probability, antitumor activity, and toxicity. The workflow was applied to identify novel ACPs with potent activity against colorectal cancer from the genome sequences of Candida albicans. As a result, four candidates were identified and validated in the HCT116 colon cancer cell line. Among them, PCa1 and PCa2 emerged as the most potent, displaying IC50 values of 3.75 and 56.06 μM, respectively, and demonstrating a 4-fold selectivity for cancer cells over normal cells. In the colon xenograft nude mice model, the administration of both peptides resulted in substantial inhibition of tumor growth without causing significant adverse effects. In conclusion, this work not only contributes a proven computational workflow for ACP discovery but also introduces two peptides, PCa1 and PCa2, as promising candidates poised for further development as targeted therapies for colon cancer. The method as a web service is available at https://app.cbbio.online/acpep/home and the source code at https://github.com/cartercheong/AcPEP_classification.git.

Synthesis and Structure of Novel Phenothiazine Derivatives, and Compound Prioritization via In Silico Target Search and Screening for Cytotoxic and Cholinesterase Modulatory Activities in Liver Cancer Cells and In Vivo in Zebrafish.

Phenothiazines (PTZ) are antipsychotics known to modulate a variety of neurotransmitter activities that include dopaminergic and cholinergic signaling and have been identified as potential anticancer agents in vitro. However, it is important to also test whether a highly cytotoxic, repurposed, or novel PTZ has low toxicity and neuromodulatory activity in vivo using vertebrate model organisms, such as zebrafish. In this study, we synthesized novel phenothiazines and screened them in vitro in liver cancer and in vivo in zebrafish embryos/larvae. The syntheses of several intermediate PTZ 10-yl acyl chlorides were followed by elemental analysis and determination of 1H NMR and 13C NMR mass (ESI+) spectra of a large number of novel PTZ 10-carboxamides. Cytotoxicities of 28 PTZ derivatives (1-28) screened against Hep3B and SkHep1 liver cancer cell lines revealed five intermediate and five novel leads along with trifluoperazine (TFP), prochlorperazine (PCP), and perphenazine, which are relatively more cytotoxic than the basic PTZ core. Overall, the derivatives were more cytotoxic to Hep3B than SkHep1 cells. Moreover, in silico target screening identified cholinesterases as some of the commonest targets of the screened phenothiazines. Interestingly, molecular docking studies with acetylcholinesterase (AChE) and butyrylcholinesterase proteins showed that the most cytotoxic compounds 1, 3, PCP, and TFP behaved similar to Huprin W in their amino acid interactions with the AChE protein. The highly cytotoxic intermediate PTZ derivative 1 exhibited a relatively lower toxicity profile than those of 2 and 3 during the zebrafish development. It also modulated in vivo the cholinesterase activity in a dose-dependent manner while significantly increasing the total cholinesterase activity and/or ACHE mRNA levels, independent of the liver cancer cell type. Our screen also identified novel phenothiazines, i.e., 8 and 10, with significant cytotoxic and cholinesterase modulatory effects in liver cancer cells; yet both compounds had low levels of toxicity in zebrafish. Moreover, they modulated the cholinesterase activity or expression of ACHE in a cancer cell line-specific manner, and compound 10 significantly inhibited the cholinesterase activity in zebrafish. Accordingly, using a successful combination of in silico, in vitro, and in vivo approaches, we identified several lead anticancer and cholinesterase modulatory PTZ derivatives for future research.

Analysis of Drug-Like Properties and in Silico Screening for the Potential of Flavonoid Compounds in Bay Leaves (Syzygium polyanthum (Wight) Walp) as Antidyslipidemia

Analysis of Drug-Like Properties and in Silico Screening for the Potential of Flavonoid Compounds in Bay Leaves (Syzygium polyanthum (Wight) Walp) as Antidyslipidemia

In Silico Screening of the Potential of Flavonoid Compounds (Rutin and Catechin) in Gardenia (Gardenia augusta, Merr.) Leaves as Antidyslipidemia

In Silico Screening of the Potential of Flavonoid Compounds (Rutin and Catechin) in Gardenia (Gardenia augusta, Merr.) Leaves as Antidyslipidemia

In Silico Screening of Bioactive Peptides in Stout Beer and Analysis of ACE Inhibitory Activity.

Stout beer was selected as the research object to screen angiotensin-converting enzyme (ACE) inhibitory peptides. The peptide sequences of stout beer were identified using ultra-performance liquid chromatography-quadrupole-Orbitrap mass spectrometry with de novo, and 41 peptides were identified with high confidence. Peptide Ranker was used to score the biological activity and six peptides with a score ≥ 0.5 were screened to predict their potential ACE inhibitory (ACEI) activity. The toxicity, hydrophilicity, absorption, and excretion of these peptides were predicted. In addition, molecular docking between the peptides and ACE revealed a significant property of the peptide DLGGFFGFQR. Furthermore, molecular docking conformation and molecular dynamics simulation revealed that DLGGFFGFQR could be tightly bound to ACE through hydrogen bonding and hydrophobic interaction. Lastly, the ACEI activity of DLGGFFGFQR was confirmed using in vitro evaluation and the IC50 value was determined to be 24.45 μM.

In Silico Screening Accelerates Nanocarrier Design for Efficient mRNA Delivery.

Lipidic nanocarriers are a broad class of lipid-based vectors with proven potential for packaging and delivering emerging nucleic acid therapeutics. An important early step in the clinical development cycle is large-scale screening of diverse formulation libraries to assess particle quality and payload delivery efficiency. Due to the size of the screening space, this process can be both costly and time-consuming. To address this, computational models capable of predicting clinically relevant physio-chemical properties of dendrimer-lipid nanocarriers, along with their mRNA payload delivery efficiency in human cells are developed. The models are then deployed on a large theoretical nanocarrier pool consisting of over 4.5 million formulations. Top predictions are synthesised for validation using cell-based assays, leading to the discovery of a high quality, high performing, candidate. The methods reported here enable rapid, high-throughput, in silico pre-screening for high-quality candidates, and have great potential to reduce the cost and time required to bring mRNA therapies to theclinic.

Impact of Model Selection and Conformational Effects on the Descriptors for In Silico Screening Campaigns: A Case Study of Rh-Catalyzed Acrylate Hydrogenation

Impact of Model Selection and Conformational Effects on the Descriptors for In Silico Screening Campaigns: A Case Study of Rh-Catalyzed Acrylate Hydrogenation