Computer-aided Drug Design Approaches Research Articles

Exploring Lead-Like Molecules of Traditional Chinese Medicine for Treatment Quest against Aliarcobacter butzleri: In Silico Toxicity Assessment, Dynamics Simulation, and Pharmacokinetic Profiling

Background. Aliarcobacter butzleri is a Gram-negative, curved or spiral-shaped, microaerophilic bacterium and causes human infections, specifically diarrhea, fever, and sepsis. The research objective of this study was to employ computer-aided drug design techniques to identify potential natural product inhibitors of a vital enzyme in this bacterium. The pyrimidine biosynthesis pathway in its core genome fraction is crucial for its survival and presents a potential target for novel therapeutics. Hence, novel small molecule inhibitors were identified (from traditional Chinese medicinal (TCM) compound library) against it, which may be used for possible curbing of infection by A. butzleri. Methods. A comprehensive subtractive genomics approach was utilized to identify a key enzyme (orotidine-5′-phosphate decarboxylase) cluster conserved in the core genome fraction of A. butzleri. It was selected for inhibitor screening due to its vital role in pyrimidine biosynthesis. TCM library (n>36,000 compounds) was screened against it using pharmacophore model based on orotidylic acid (control), and the obtained lead-like molecules were subjected to structural docking using AutoDock Vina. The top-scoring compounds, ZINC70454134, ZINC85632684, and ZINC85632721, underwent further scrutiny via a combination of physiological-based pharmacokinetics, toxicity assessment, and atomic-scale dynamics simulations (100 ns). Results. Among the screened compounds, ZINC70454134 displayed the most favorable characteristics in terms of binding, stability, absorption, and safety parameters. Overall, traditional Chinese medicine (TCM) compounds exhibited high bioavailability, but in diseased states (cirrhosis, renal impairment, and steatosis), there was a significant decrease in absorption, Cmax, and AUC of the compounds compared to the healthy state. Furthermore, MD simulation demonstrated that the ODCase-ZINC70454134 complex had a superior overall binding affinity, supported by PCA proportion of variance and eigenvalue rank analysis. These favorable characteristics underscore its potential as a promising drug candidate. Conclusion. The computer-aided drug design approach employed for this study helped expedite the discovery of antibacterial compounds against A. butzleri, offering a cost-effective and efficient approach to address infection by it. It is recommended that ZINC70454134 should be considered for further experimental analysis due to its indication as a potential therapeutic agent for combating A. butzleri infections. This study provides valuable insights into the molecular basis of biophysical inhibition of A. butzleri through TCM compounds.

Targeting with Structural Analogs of Natural Products the Purine Salvage Pathway in Leishmania (Leishmania) infantum by Computer-Aided Drug-Design Approaches.

Visceral Leishmaniasis (VL) has a high death rate, with 500,000 new cases and 50,000 deaths occurring annually. Despite the development of novel strategies and technologies, there is no adequate treatment for the disease. Therefore, the purpose of this study is to find structural analogs of natural products as potential novel drugs to treat VL. We selected structural analogs from natural products that have shown antileishmanial activities, and that may impede the purine salvage pathway using computer-aided drug-design (CADD) approaches. For these, we started with the vastly studied target in the pathway, the adenine phosphoribosyl transferase (APRT) protein, which alone is non-essential for the survival of the parasite. Keeping this in mind, we search for a substance that can bind to multiple targets throughout the pathway. Computational techniques were used to study the purine salvage pathway from Leishmania infantum, and molecular dynamic simulations were used to gather information on the interactions between ligands and proteins. Because of its low homology to human proteins and its essential role in the purine salvage pathway proteins network interaction, the findings further highlight the significance of adenylosuccinate lyase protein (ADL) as a therapeutic target. An analog of the alkaloid Skimmianine, N,N-diethyl-4-methoxy-1-benzofuran-6-carboxamide, demonstrated a good binding affinity to APRT and ADL targets, no expected toxicity, and potential for oral route administration. This study indicates that the compound may have antileishmanial activity, which was granted in vitro and in vivo experiments to settle this finding in the future.

Design of new small molecules derived from indolin-2-one as potent TRKs inhibitors using a computer-aided drug design approach

Tropomyosin receptor kinase (TRKs) enzymes are responsible for cancers associated with the neurotrophic tyrosine kinase receptor gene fusion and are identified as effective targets for anticancer drug discovery. A series of small-molecule indolin-2-one derivatives showed remarkable biological activity against TRKs enzymatic activity. These small molecules could have an excellent profile for pharmaceutical application in the treatment of cancers caused by TRKs activity. The aim of this study is to modify the structure of these molecules to obtain new molecules with improved TRK inhibitory activity and pharmacokinetic properties favorable to the design of new drugs. Based on these series, we carried out a 3D-QSAR study. As a result, robust and reliable CoMFA and CoMSIA models are developed and applied to the design of 11 new molecules. These new molecules have a biological activity superior to the most active molecule in the starting series. The eleven designed molecules are screened using drug-likeness, ADMET proprieties, molecular docking, and MM-GBSA filters. The results of this screening identified the T1, T3, and T4 molecules as the best candidates for strong inhibition of TRKs enzymatic activity. In addition, molecular dynamics simulations are performed for TRK free and complexed with ligands T1, T3, and T4 to evaluate the stability of ligand-protein complexes over the simulation time. On the other hand, we proposed experimental synthesis routes for these newly designed molecules. Finally, the designed molecules T1, T2, and T3 have great potential to become reliable candidates for the conception of new drug inhibitors of TRKs. Communicated by Ramaswamy H. Sarma

Dual Targeting of DNA Damage Response Proteins Implicated in Cancer Radioresistance.

Ionizing radiation can induce different types of DNA lesions, leading to genomic instability and ultimately cell death. Radiation therapy or radiotherapy, a major modality in cancer treatment, harnesses the genotoxic potential of radiation to target and destroy cancer cells. Nevertheless, cancer cells have the capacity to develop resistance to radiation treatment (radioresistance), which poses a major obstacle in the effective management of cancer. It has been shown that administration of platinum-based drugs to cancer patients can increase tumor radiosensitivity, but despite this, it is associated with severe adverse effects. Several lines of evidence support that activation of the DNA damage response and repair machinery in the irradiated cancer cells enhances radioresistance and cellular survival through the efficient repair of DNA lesions. Therefore, targeting of key DNA damage repair factors would render cancer cells vulnerable to the irradiation effects, increase cancer cell killing, and reduce the risk of side effects on healthy tissue. Herein, we have employed a computer-aided drug design approach for generating ab initio a chemical compound with drug-like properties potentially targeting two proteins implicated in multiple DNA repair pathways. The findings of this study could be taken into consideration in clinical decision-making in terms of co-administering radiation with DNA damage repair factor-based drugs.

Identification of potential inhibitors targeting Ebola virus VP35 protein: a computational strategy

Ebola virus (EBOV) poses a severe threat as a highly infectious pathogen, causing devastating hemorrhagic fever in both humans and animals. The EBOV virus VP35 protein plays a crucial role in viral replication and exhibits the ability to suppress the host interferon cascade, leading to immune system depletion. As a potential drug target, VP35 protein inhibition holds promise for combating EBOV. To discover new drug candidates, we employed a computer-aided drug design approach, focusing on compounds capable of inhibiting VP35 protein replication. In this connection, a pharmacophore model was generated using molecular interactions between the VP35 protein and its inhibitor. ZINC and Cambridge database were screened using validated pharmacophore model. Further the compounds were filtered based on Lipinski’s rule of five and subjected to MD simulation and relative binding free energy calculation. Six compounds manifest a significant docking score and strong binding interaction towards VP35 protein. MD simulations further confirmed the remarkable stability of these six complexes. Relative binding free energy calculations also showed significant ΔG value in the range of −132.3 and −49.3 kcal/mol. This study paves the way for further optimization of these compounds as potential inhibitors of VP35, facilitating subsequent experimental in vitro studies. Communicated by Ramaswamy H. Sarma

Antibreast cancer activities of phytochemicals from Anonna muricata using computer-aided drug design (CADD) approach

Abstract Antibreast cancer activities of 131 phytochemicals from Annona muricata (Soursop) were investigated against human placental aromatase (PDB ID: 3S7S), a prominent target receptor in breast cancer therapy using computer aided-drug design approach. An antibreast cancer drug (tamoxifen) was used for comparison. The result of this work flourishes caffeoquinic acid (−8.4 kcal/mol), roseoside (−8.3 kcal/mol), chlorogenic acid (−8.2 kcal/mol), feruloylglycoside (−8.1 kcal/mol), citroside A (−8.0 kcal/mol), and coreximine (−7.8 kcal/mol), as probable inhibitors of human placental aromatase. This is due to their excellent binding affinities (ΔG), coupled with outstanding druglike, absorption, distribution, metabolism, excretion, and toxicity profiles, bioavailability and oral-bioavailability properties, and the interactions of important residues with the active pocket of human placental aromatase. All the results obtained were similar to that of the standards tamoxifen (−8.0 kcal/mol) but could be better when optimized. Thus, lead optimization, molecular dynamics, and in vivo investigations are thereby recommended on the identified potent compounds in the quest of developing new therapeutic agents against breast cancer.

An Exploration of the Inhibitory Mechanism of Rationally Screened Benzofuran-1,3,4-Oxadiazoles and-1,2,4-Triazoles as Inhibitors of NS5B RdRp Hepatitis C Virus through Pharmacoinformatic Approaches.

Benzofuran, 1,3,4-oxadiazole, and 1,2,4-triazole are privileged heterocyclic moieties that display the most promising and wide spectrum of biological activities against a wide variety of diseases. In the current study, benzofuran-1,3,4-oxadiazole BF1-BF7 and benzofuran-1,2,4-triazole compounds BF8-BF15 were tested against HCV NS5B RNA-dependent RNA polymerase (RdRp) utilizing structure-based screening via a computer-aided drug design (CADD) approach. A molecular docking approach was applied to evaluate the binding potential of benzofuran-appended 1,3,4-oxadiazole and 1,2,4-triazole BF1-BF15 molecules. Benzofuran-1,3,4-oxadiazole scaffolds BF1-BF7 showed lesser binding affinities (-12.63 to -14.04 Kcal/mol) than benzofuran-1,2,4-triazole scaffolds BF8-BF15 (-14.11 to -16.09 Kcal/mol) against the HCV NS5B enzyme. Molecular docking studies revealed the excellent binding affinity scores exhibited by benzofuran-1,2,4-triazole structural motifs BF-9 (-16.09 Kcal/mol), BF-12 (-15.75 Kcal/mol), and BF-13 (-15.82 Kcal/mol), respectively, which were comparatively better than benzofuran-based HCV NS5B inhibitors' standard reference drug Nesbuvir (-15.42 Kcal/mol). A molecular dynamics simulation assay was also conducted to obtain valuable insights about the enzyme-compounds interaction profile and structural stability, which indicated the strong intermolecular energies of the BF-9+NS5B complex and the BF-12+NS5B complex as per the MM-PBSA method, while the BF-12+NS5B complex was the most stable system as per the MM-GBSA calculation. The drug-likeness and ADMET studies of all the benzofuran-1,2,4-triazole derivatives BF8-BF15 revealed that these compounds possessed good medicinal chemistry profiles in agreement with all the evaluated parameters for being drugs. The molecular docking affinity scores, MM-PBSA/MM-GBSA and MD-simulation stability analysis, drug-likeness profiling, and ADMET study assessment indicated that N-4-fluorophenyl-S-linked benzofuran-1,2,4-triazole BF-12 could be a future promising anti-HCV NS5B RdRp inhibitor therapeutic drug candidate that has a structural agreement with the Nesbuvir standard reference drug.

Design, Synthesis, Evaluation and Molecular Dynamics Simulation of Dengue Virus NS5-RdRp Inhibitors.

Dengue virus (DENV) is a major mosquito-borne human pathogen in tropical countries; however, there are currently no targeted antiviral treatments for DENV infection. Compounds 27 and 29 have been reported to be allosteric inhibitors of DENV RdRp with potent inhibitory effects. In this study, the structures of compounds 27 and 29 were optimized using computer-aided drug design (CADD) approaches. Nine novel compounds were synthesized based on rational considerations, including molecular docking scores, free energy of binding to receptor proteins, predicted Absorption, Distribution, Metabolism, Excretion, and Toxicity (ADMET) parameters, structural diversity, and feasibility of synthesis. Subsequently, the anti-DENV activity was assessed. In the cytopathic effect (CPE) assay conducted on BHK-21 cells using the DENV2 NGC strain, both SW-b and SW-d demonstrated comparable or superior activity against DENV2, with IC50 values of 3.58 ± 0.29 μM and 23.94 ± 1.00 μM, respectively, compared to that of compound 27 (IC50 = 19.67 ± 1.12 μM). Importantly, both SW-b and SW-d exhibited low cytotoxicity, with CC50 values of 24.65 μmol and 133.70 μmol, respectively, resulting in selectivity indices of 6.89 and 5.58, respectively. Furthermore, when compared to the positive control compound 3'-dATP (IC50 = 30.09 ± 8.26 μM), SW-b and SW-d displayed superior inhibitory activity in an enzyme inhibitory assay, with IC50 values of 11.54 ± 1.30 μM and 13.54 ± 0.32 μM, respectively. Molecular dynamics (MD) simulations elucidated the mode of action of SW-b and SW-d, highlighting their ability to enhance π-π packing interactions between benzene rings and residue W795 in the S1 fragment, compared to compounds 27 and 29. Although the transacylsulphonamide fragment reduced the interaction between T794 and NH, it augmented the interaction between R729 and T794. In summary, our study underscores the potential of SW-b and SW-d as allosteric inhibitors targeting the DENV NS5 RdRp domain. However, further in vivo studies are warranted to assess their pharmacology and toxicity profiles.

An Updated Review on Developing Small Molecule Kinase Inhibitors Using Computer-Aided Drug Design Approaches.

Small molecule kinase inhibitors (SMKIs) are of heightened interest in the field of drug research and development. There are 79 (as of July 2023) small molecule kinase inhibitors that have been approved by the FDA and hundreds of kinase inhibitor candidates in clinical trials that have shed light on the treatment of some major diseases. As an important strategy in drug design, computer-aided drug design (CADD) plays an indispensable role in the discovery of SMKIs. CADD methods such as docking, molecular dynamic, quantum mechanics/molecular mechanics, pharmacophore, virtual screening, and quantitative structure-activity relationship have been applied to the design and optimization of small molecule kinase inhibitors. In this review, we provide an overview of recent advances in CADD and SMKIs and the application of CADD in the discovery of SMKIs.

The importance of good practices and false hits for QSAR-driven virtual screening real application: a SARS-CoV-2 main protease (Mpro) case study

Computer-Aided Drug Design (CADD) approaches, such as those employing quantitative structure-activity relationship (QSAR) methods, are known for their ability to uncover novel data from large databases. These approaches can help alleviate the lack of biological and chemical data, but some predictions do not generate sufficient positive information to be useful for biological screenings. QSAR models are often employed to explain biological data of chemicals and to design new chemicals based on their predictions. In this review, we discuss the importance of data set size with a focus on false hits for QSAR approaches. We assess the challenges and reliability of an initial in silico strategy for the virtual screening of bioactive molecules. Lastly, we present a case study reporting a combination approach of hologram-based quantitative structure-activity relationship (HQSAR) models and random forest-based QSAR (RF-QSAR), based on the 3D structures of 25 synthetic SARS-CoV-2 Mpro inhibitors, to virtually screen new compounds for potential inhibitors of enzyme activity. In this study, optimal models were selected and employed to predict Mpro inhibitors from the database Brazilian Compound Library (BraCoLi). Twenty-four compounds were then assessed against SARS-CoV-2 Mpro at 10 µM. At the time of this study (March 2021), the availability of varied and different Mpro inhibitors that were reported definitely affected the reliability of our work. Since no hits were obtained, the data set size, parameters employed, external validations, as well as the applicability domain (AD) could be considered regarding false hits data contribution, aiming to enhance the design and discovery of new bioactive molecules.

Computer-aided drug design approaches applied to screen natural product’s structural analogs targeting arginase in Leishmania spp

Introduction: Leishmaniasis is a disease with high mortality rates and approximately 1.5 million new cases each year. Despite the new approaches and advances to fight the disease, there are no effective therapies. Methods: Hence, this study aims to screen for natural products' structural analogs as new drug candidates against leishmaniasis. We applied Computer-aided drug design (CADD) approaches, such as virtual screening, molecular docking, molecular dynamics simulation, molecular mechanics–generalized Born surface area (MM–GBSA) binding free estimation, and free energy perturbation (FEP) aiming to select structural analogs from natural products that have shown anti-leishmanial and anti-arginase activities and that could bind selectively against the Leishmania arginase enzyme. Results: The compounds 2H-1-benzopyran, 3,4-dihydro-2-(2-methylphenyl)-(9CI), echioidinin, and malvidin showed good results against arginase targets from three parasite species and negative results for potential toxicities. The echioidinin and malvidin ligands generated interactions in the active center at pH 2.0 conditions by MM-GBSA and FEP methods. Conclusions: This work suggests the potential anti-leishmanial activity of the compounds and thus can be further in vitro and in vivo experimentally validated.

Medicinal and toxicological investigation of some common NSAIDs; A computer-aided drug design approach

Nonsteroidal anti-inflammatory drugs (NSAIDs) are commonly used for the treatment of pain, fever, and inflammation. Their consumption rises some crucial side effects like gastrointestinal, cardiovascular, and renal injury because of the non-selective reduction of prostaglandin synthesis, with differences in the extent of inhibition of the cyclooxygenase. Attempts have been taken for a comparative biochemical, medicinal, and toxicological investigation to raise awareness of the consumption of NSAIDs. In-silico methods were incorporated to investigate their physicochemical, spectral, medicinal, pharmacological, and toxicological properties. Molecular docking and non-bonding calculations were performed against the human prostaglandin synthase protein to reveal their binding affinity and interactions with the amino acid residues of the receptor protein. Further, molecular dynamics simulation was conducted to validate the binding mode and drug-protein stability at the inhibiting binding pocket. The physical and chemical analysis supports their geometries and spectral results confirming the presence of essential functional groups at the core structure. From ADMET and PASS prediction, all the drugs are non-carcinogenic (except IBP), and nonselective NSAIDs showed relatively higher adverse effects compared to selective agents. Based on the above studies, this report can be helpful to understand more deeply the medicinal, and toxicological effects of the reported NSAIDs.

Discovery of thiazolo[5,4-c]isoquinoline based compounds as acetylcholinesterase inhibitors through computational target prediction, molecular docking and bioassay

A computer-aided drug design (CADD) approach was developed for a focused chemical library comprising a series of sixteen thiazolo[5,4-c]isoquinoline derivatives. Little is known about this group of heteroaromatic compounds, both from the point of view of their synthesis and their biological properties. First, our CADD approach included target prediction by Mondrian conformal prediction with the ChEMBL database. The acetylcholinesterase (AChE) was identified as having a high probability of thiazolo[5,4-c]isoquinolines being active against it. Secondly, the molecular docking predictions revealed four promising thiazoloisoquinolines (2, 7, 13 and 14) according to their prominent ligand-protein energy scores and relevant binding affinities with the AChE pocket residues. The subsequent in vitro evaluation of promising hits and related ones revealed a set of novel AChE inhibitors. Therefore, the findings reported herein may provide a new strategy for discovering novel AChE inhibitors.

In Silico Development of Novel Benzofuran-1,3,4-Oxadiazoles as Lead Inhibitors of M. tuberculosis Polyketide Synthase 13.

Benzofuran and 1,3,4-oxadiazole are privileged and versatile heterocyclic pharmacophores which display a broad spectrum of biological and pharmacological therapeutic potential against a wide variety of diseases. This article reports in silico CADD (computer-aided drug design) and molecular hybridization approaches for the evaluation of the chemotherapeutic efficacy of 16 S-linked N-phenyl acetamide moiety containing benzofuran-1,3,4-oxadiazole scaffolds BF1-BF16. This virtual screening was carried out to discover and assess the chemotherapeutic efficacy of BF1-BF16 structural motifs as Mycobacterium tuberculosis polyketide synthase 13 (Mtb Pks13) enzyme inhibitors. The CADD study results revealed that the benzofuran clubbed oxadiazole derivatives BF3, BF4, and BF8 showed excellent and remarkably significant binding energies against the Mtb Pks13 enzyme comparable with the standard benzofuran-based TAM-16 inhibitor. The best binding affinity scores were displayed by 1,3,4-oxadiazoles-based benzofuran scaffolds BF3 (-14.23 kcal/mol), BF4 (-14.82 kcal/mol), and BF8 (-14.11 kcal/mol), in comparison to the binding affinity score of the standard reference TAM-16 drug (-14.61 kcal/mol). 2,5-Dimethoxy moiety-based bromobenzofuran-oxadiazole derivative BF4 demonstrated the highest binding affinity score amongst the screened compounds, and was higher than the reference Pks13 inhibitor TAM-16 drug. The bindings of these three leads BF3, BF4, and BF8 were further confirmed by the MM-PBSA investigations in which they also exhibited strong bindings with the Pks13 of Mtb. Moreover, the stability analysis of these benzofuran-1,3,4-oxadiazoles in the active sites of the Pks13 enzyme was achieved through molecular dynamic (MD) simulations at 250 ns virtual simulation time, which indicated that these three in silico predicted bio-potent benzofuran tethered oxadiazole molecules BF3, BF4, and BF8 demonstrated stability with the active site of the Pks13 enzyme.

Identification of novel inhibitors of P13K/AKT pathways: an integrated in-silico study towards the development of a new therapeutic agent against ovarian cancer

Abstract Ovarian cancer is a crucial gynaecological unmet medical disease with a high mortality rate. According to recent research, the phosphoinositol 3 kinase (PI3K)/protein kinase B (AKT)/mammalian target of rapamycin (mTOR) pathways are hyper-activated in the majority of ovarian cancer patients, necessitating the use of inhibitors. Over the years, phytochemicals have been used as alternative sources of therapeutic agents due to their reported biological activities and limited side effects. Curcuma longa (Tumeric), a reported ayurvedic medicine has also been noted for its anti-cancer properties. Thus, 155 phytochemicals from this plant and 2 reference drugs were evaluated for their inhibitory prowess against P13K/AKT receptor using a computer-aided drug design approach. The binding scores and inhibiting efficiencies were obtained via virtual screening. Molinspiration Chemoinformatics and SwissADME tools were used to investigate the drug-likeness properties and oral bioavailability of the compounds selected, while the ADMET SAR-2 website was used to conduct the Absorption, Distribution, Metabolism, Excretion, and Toxicity (ADMET) analysis. Other analyses performed on the selected compounds include bioactivity, activity spectra for substances (PASS) prediction, binding mode, and molecular interaction. The results revealed that Hopenone 1 (−8.8 kcal mol−1) and Epriprocurcumenol (−7.8 kcal mol−1) are potent inhibitors of the P13K receptor, while Epiprocurcumenol (−9.0 kcal mol−1), Procurcuminol (−8.6 kcal mol−1) and Curlone (−8.3 kcal mol−1) are potential inhibitors of AKT receptor. In comparison to Topotecan and Melphalan, they have better binding affinities, oral bioavailability, drug-likeness characteristics, ADMET properties, bioactivities, PASS properties, binding mechanism, and also interact well with the active site of the target receptor. As a result, this preliminary investigation suggests that these chemicals should be studied further for the design of novel ovarian cancer therapeutics.

Computer-aided drug design approaches applied toscreen natural product's structural analogs targeting arginase in Leishmania spp.

Introduction: Leishmaniasis is a disease with high mortality rates and approximately 1.5 million new cases each year. Despite the new approaches and advances to fight the disease, there are no effective therapies. Methods: Hence, this study aims to screen for natural products' structural analogs as new drug candidates against leishmaniasis. We applied Computer-aided drug design (CADD) approaches, such as virtual screening, molecular docking, molecular dynamics simulation, molecular mechanics-generalized Born surface area (MM-GBSA) binding free estimation, and free energy perturbation (FEP) aiming to select structural analogs from natural products that have shown anti-leishmanial and anti-arginase activities and that could bind selectively against the Leishmania arginase enzyme. Results: The compounds 2H-1-benzopyran, 3,4-dihydro-2-(2-methylphenyl)-(9CI), echioidinin, and malvidin showed good results against arginase targets from three parasite species and negative results for potential toxicities. The echioidinin and malvidin ligands generated interactions in the active center at pH 2.0 conditions by MM-GBSA and FEP methods. Conclusions: This work suggests the potential anti-leishmanial activity of the compounds and thus can be further in vitro and in vivo experimentally validated.

Virtual Screening Algorithms in Drug Discovery: A Review Focused on Machine and Deep Learning Methods

Drug discovery and repositioning are important processes for the pharmaceutical industry. These processes demand a high investment in resources and are time-consuming. Several strategies have been used to address this problem, including computer-aided drug design (CADD). Among CADD approaches, it is essential to highlight virtual screening (VS), an in silico approach based on computer simulation that can select organic molecules toward the therapeutic targets of interest. The techniques applied by VS are based on the structure of ligands (LBVS), receptors (SBVS), or fragments (FBVS). Regardless of the type of VS to be applied, they can be divided into categories depending on the used algorithms: similarity-based, quantitative, machine learning, meta-heuristics, and other algorithms. Each category has its objectives, advantages, and disadvantages. This review presents an overview of the algorithms used in VS, describing them and showing their use in drug design and their contribution to the drug development process.

Pharmacophore-based virtual screening, molecular docking and molecular dynamics simulation for identification of potential ERK inhibitors

As the downstream component of the mitogen-activated protein kinases (MAPK) pathway, the extracellular signal-regulated kinase (ERK) is responsible for phosphorylating a broad range of substrates in cell proliferation, differentiation, and survival. Direct targeting the ERK proteins by the piperidinopyrimidine urea-based inhibitors has been demonstrated to be an effective way to block the MAPK signaling pathway in inhibiting tumor growth. In order to discover better inhibitors, a computer-aided drug design (CADD) approach was employed to reveal the pharmacological characteristics and mechanisms of action. The pharmacophore model was generated on the basis of the compounds with eight features, i.e., four hydrogen bond acceptor atoms, one hydrogen bond donor atom, and three hydrophobic centers. A total of 14 hit compounds were obtained through virtual screening. Two potential inhibitors, namely VS01 and VS02, have been identified by molecular docking and molecular dynamics simulations. Both compounds are capable of attaching to the ERK pocket precisely. The binding free energies of VS01 and VS02 are about 15 kJ/mol and 4 kJ/mol stronger than that of the clinic Ulixertinib because of the characteristic hydrogen bonding, electrostatic, and hydrophilic interactions. The present theoretical investigations shed new light on the rational design of the potential ERK inhibitors to stimulate further experimental tests. Communicated by Ramaswamy H. Sarma

Key ingredients in Verbena officinalis and determination of their anti-atherosclerotic effect using a computer-aided drug design approach.

Lipid metabolism disorders may considerably contribute to the formation and development of atherosclerosis (AS). Traditional Chinese medicine has received considerable attention in recent years owing to its ability to treat lipid metabolism disorders using multiple components and targets. Verbena officinalis (VO), a Chinese herbal medicine, exhibits anti-inflammatory, analgesic, immunomodulatory, and neuroprotective effects. Evidence suggests that VO regulates lipid metabolism; however, its role in AS remains unclear. In the present study, an integrated network pharmacology approach, molecular docking, and molecular dynamics simulation (MDS) were applied to examine the mechanism of VO against AS. Analysis revealed 209 potential targets for the 11 main ingredients in VO. Further, 2698 mechanistic targets for AS were identified, including 147 intersection targets between VO and AS. Quercetin, luteolin, and kaempferol were considered key ingredients for the treatment of AS based on a potential ingredient target-AS target network. GO analysis revealed that biological processes were primarily associated with responses to xenobiotic stimuli, cellular responses to lipids, and responses to hormones. Cell components were predominantly focused on the membrane microdomain, membrane raft, and caveola nucleus. Molecular functions were mainly focused on DNA-binding transcription factor binding, RNA polymerase II-specific DNA-binding transcription factor binding, and transcription factor binding. KEGG pathway enrichment analysis identified pathways in cancer, fluid shear stress, and atherosclerosis, with lipid and atherosclerosis being the most significantly enriched pathways. Molecular docking revealed that three key ingredients in VO (i.e., quercetin, luteolin, and kaempferol) strongly interacted with three potential targets (i.e., AKT1, IL-6, and TNF-α). Further, MDS revealed that quercetin had a stronger binding affinity for AKT1. These findings suggest that VO has beneficial effects on AS via these potential targets that are closely related to the lipid and atherosclerosis pathways. Our study utilized a new computer-aided drug design to identify key ingredients, potential targets, various biological processes, and multiple pathways associated with the clinical roles of VO in AS, which provides a comprehensive and systemic pharmacological explanation for the anti-atherosclerotic activity of VO.

Targeting Toxoplasma gondii ME49 TgAPN2: A Bioinformatics Approach for Antiparasitic Drug Discovery.

As fewer therapeutic options are available for treating toxoplasmosis, newer antiparasitic drugs that can block TgAPN2 M1 aminopeptidase are of significant value. Herein, we employed several computer-aided drug-design approaches with the objective of identifying drug molecules from the Asinex library with stable conformation and binding energy scores. By a structure-based virtual screening process, three molecules-LAS_52160953, LAS_51177972, and LAS_52506311-were identified as promising candidates, with binding affinity scores of -8.6 kcal/mol, -8.5 kcal/mol, and -8.3 kcal/mol, respectively. The compounds produced balanced interacting networks of hydrophilic and hydrophobic interactions, vital for holding the compounds at the docked cavity and stable binding conformation. The docked compound complexes with TgAPN2 were further subjected to molecular dynamic simulations that revealed mean RMSD for the LAS_52160953 complex of 1.45 Å), LAS_51177972 complex 1.02 Å, and LAS_52506311 complex 1.087 Å. Another round of binding free energy validation by MM-GBSA/MM-PBSA was done to confirm docking and simulation findings. The analysis predicted average MM-GBSA value of <-36 kcal/mol and <-35 kcal/mol by MM-PBSA. The compounds were further classified as appropriate candidates to be used as drug-like molecules and showed favorable pharmacokinetics. The shortlisted compounds showed promising biological potency against the TgAPN2 enzyme and may be used in experimental validation. They may also serve as parent structures to design novel derivatives with enhanced biological potency.