In Silico Drug Repurposing Approach: Investigation of Mycobacterium tuberculosis FadD32 Targeted by FDA-Approved Drugs

Background: Despite the enormous efforts made towards combating tuberculosis (TB), the disease remains a major global threat. Hence, new drugs with novel mechanisms against TB are urgently needed. Fatty acid degradation protein D32 (FadD32) has been identified as a promising drug target against TB, the protein is required for the biosynthesis of mycolic acids, hence, essential for the growth and multiplication of the mycobacterium. However, the FadD32 mechanism upon the binding of FDA-approved drugs is not well established. Herein, we applied virtual screening (VS), molecular docking, and molecular dynamic (MD) simulation to identify potential FDA-approved drugs against FadD32. Methodology/Results: VS technique was found promising to identify four FDA-approved drugs (accolate, sorafenib, mefloquine, and loperamide) with higher molecular docking scores, ranging from −8.0 to −10.0 kcal/mol. Post-MD analysis showed that the accolate hit displayed the highest total binding energy of −45.13 kcal/mol. Results also showed that the accolate hit formed more interactions with FadD32 active site residues and all active site residues displayed an increase in total binding contribution. RMSD, RMSF, Rg, and DCCM analysis further supported that the presence of accolate exhibited more structural stability, lower bimolecular flexibility, and more compactness into the FadD32 protein. Conclusions: Our study revealed accolate as the best potential drug against FadD32, hence a prospective anti-TB drug in TB therapy. In addition, we believe that the approach presented in the current study will serve as a cornerstone to identifying new potential inhibitors against a wide range of biological targets.     

In Silico Drug Repurposing of FDA-Approved Drugs Highlighting Promacta as a Potential Inhibitor of H7N9 Influenza Virus

Influenza virus infections continue to be a significant and recurrent public health problem. Although vaccine efficacy varies, regular immunisation is the most effective method for suppressing the influenza virus. Antiviral drugs are available for influenza, although two of the four FDA-approved antiviral treatments have resulted in significant drug resistance. Therefore, new treatments are being sought to reduce the burden of flu-related illness. The time-consuming development of treatments for new and re-emerging diseases such as influenza and the high failure rate are increasing concerns. In this context, we used an in silico-based drug repurposing method to repurpose FDA-approved drugs as potential therapies against the H7N9 virus. To find potential inhibitors, a total of 2568 drugs were screened. Promacta, tucatinib, and lurasidone were identified as promising hits in the DrugBank database. According to the calculations of MM-GBSA, tucatinib (−54.11 kcal/mol) and Promacta (−56.20 kcal/mol) occupied the active site of neuraminidase with a higher binding affinity than the standard drug peramivir (−49.09 kcal/mol). Molecular dynamics (MD) simulation studies showed that the C-α atom backbones of the complexes of tucatinib and Promacta neuraminidase were stable throughout the simulation period. According to ADME analysis, the hit compounds have a high gastrointestinal absorption (GI) and do not exhibit properties that allow them to cross the blood–brain barrier (BBB). According to the in silico toxicity prediction, Promacta is not cardiotoxic, while lurasidone and tucatinib show only weak inhibition. Therefore, we propose to test these compounds experimentally against the influenza H7N9 virus. The investigation and validation of these potential H7N9 inhibitors would be beneficial in order to bring these compounds into clinical settings.     

Antiviral Activity of Metabolites from Peruvian Plants against SARS-CoV-2: An In Silico Approach

(1) Background: The COVID-19 pandemic lacks treatments; for this reason, the search for potential compounds against therapeutic targets is still necessary. Bioinformatics tools have allowed the rapid in silico screening of possible new metabolite candidates from natural resources or repurposing known ones. Thus, in this work, we aimed to select phytochemical candidates from Peruvian plants with antiviral potential against three therapeutical targets of SARS-CoV-2. (2) Methods: We applied in silico technics, such as virtual screening, molecular docking, molecular dynamics simulation, and MM/GBSA estimation. (3) Results: Rutin, a compound present in Peruvian native plants, showed affinity against three targets of SARS-CoV-2. The molecular dynamics simulation demonstrated the high stability of receptor–ligand systems during the time of the simulation. Our results showed that the Mpro-Rutin system exhibited higher binding free energy than PLpro-Rutin and N-Rutin systems through MM/GBSA analysis. (4) Conclusions: Our study provides insight on natural metabolites from Peruvian plants with therapeutical potential. We found Rutin as a potential candidate with multiple pharmacological properties against SARS-CoV-2.     

Discovery of New Hits as Antitrypanosomal Agents by In Silico and In Vitro Assays Using Neolignan-Inspired Natural Products from Nectandra leucantha

In the present study, the phytochemical study of the n-hexane extract from flowers of Nectandra leucantha (Lauraceae) afforded six known neolignans (1–6) as well as one new metabolite (7), which were characterized by analysis of NMR, IR, UV, and ESI-HRMS data. The new compound 7 exhibited potent activity against the clinically relevant intracellular forms of T. cruzi (amastigotes), with an IC₅₀ value of 4.3 μM and no observed mammalian cytotoxicity in fibroblasts (CC₅₀ > 200 μM). Based on the results obtained and our previous antitrypanosomal data of 50 natural and semi-synthetic related neolignans, 2D and 3D molecular modeling techniques were employed to help the design of new neolignan-based compounds with higher activity. The results obtained from the models were important to understand the main structural features related to the biological response of the neolignans and to aid in the design of new neolignan-based compounds with better biological activity. Therefore, the results acquired from phytochemical, biological, and in silico studies showed that the integration of experimental and computational techniques consists of a powerful tool for the discovery of new prototypes for development of new drugs to treat CD.     

Impact of Genomics and in Silico Related Technologies in the Drug Discovery Process

In order to evaluate to what extent will genomics and in silico related technologies improve overall drug discovery process, we analyzed three studies comping cost, time and attrition rate at each step of the drug discovery process, between standard pharmaceutical and genomics based approaches.     

Identification of Novel Dopamine D2 Receptor Ligands—A Combined In Silico/In Vitro Approach

Diseases of the central nervous system are an alarming global problem showing an increasing prevalence. Dopamine receptor D₂ (D₂R) has been shown to be involved in central nervous system diseases. While different D₂R-targeting drugs have been approved by the FDA, they all suffer from major drawbacks due to promiscuous receptor activity leading to adverse effects. Increasing the number of potential D₂R-targeting drug candidates bears the possibility of discovering molecules with less severe side-effect profiles. In dire need of novel D₂R ligands for drug development, combined in silico/in vitro approaches have been shown to be efficient strategies. In this study, in silico pharmacophore models were generated utilizing both ligand- and structure-based approaches. Subsequently, different databases were screened for novel D₂R ligands. Selected virtual hits were investigated in vitro, quantifying their binding affinity towards D₂R. This workflow successfully identified six novel D₂R ligands exerting micro- to nanomolar (most active compound K_I = 4.1 nM) activities. Thus, the four pharmacophore models showed prospective true-positive hit rates in between 4.5% and 12%. The developed workflow and identified ligands could aid in developing novel drug candidates for D₂R-associated pathologies.     

Design and Synthesis In Silico Drug-like Prediction and Pharmacological Evaluation of Cyclopolymethylenic Homologous of LASSBio-1514

Acylhydrazones are still an important framework to the design of new bioactive compounds. As treatment of chronic pain represents a clinical challenge, we decided to modify the structure of LASSBio-1514 (1), previously described as anti-inflammatory and analgesic prototype. Applying the homologation as a strategy for molecular modification, we designed a series of cyclopentyl- (2a–e), cyclobutyl- (3a–e), and cyclopropylacylhydrazones (4a–e) that were synthetized and evaluated in murine models of inflammation and pain. A comparison of their in silico physicochemical and drug-like profile was conducted, as well as their anti-inflammatory and analgesic effect. Compounds 4a (LASSBio-1755) and 4e (LASSBio-1757) displayed excellent in silico drug-like profiles and were identified as new analgesic lead-candidates in acute and chronic model of pain, through oral administration.     

In Silico Design of a Peptide Receptor for Dopamine Recognition

Dopamine (DA) is an important neurotransmitter with a fundamental role in regulatory functions related to the central, peripheral, renal, and hormonal nervous systems. Dopaminergic neurotransmission dysfunctions are commonly associated with several diseases; thus, in situ quantification of DA is a major challenge. To achieve this goal, enzyme-based biosensors have been employed for substrate recognition in the past. However, due to their sensitivity to changes in temperature and pH levels, new peptide bioreceptors have been developed. Therefore, in this study, four bioreceptors were designed in silico to exhibit a higher affinity for DA than the DA transporters (DATs). The design was based on the hot spots of the active sites of crystallized enzyme structures that are physiologically related to DA. The affinities between the chosen targets and designed bioreceptors were calculated using AutoDock Vina. Additionally, the binding free energy, ∆G, of the dopamine-4xp1 complex was calculated by molecular dynamics (MD). This value presented a direct relationship with the E_refine value obtained from molecular docking based on the ∆G functions obtained from MOE of the promising bioreceptors. The control variables in the design were amino acids, bond type, steric volume, stereochemistry, affinity, and interaction distances. As part of the results, three out of the four bioreceptor candidates presented promising values in terms of DA affinity and distance.     

In Silico Approach of Glycinin and Conglycinin Chains of Soybean By-Product (Okara) Using Papain and Bromelain

This study explores utilization of a sustainable soybean by-product (okara) based on in silico approach. In silico approaches, as well as the BIOPEP database, PeptideRanker database, Peptide Calculator database (Pepcalc), ToxinPred database, and AllerTop database, were employed to evaluate the potential of glycinin and conglycinin derived peptides as a potential source of bioactive peptides. These major protein precursors have been found as protein in okara as a soybean by-product. Furthermore, primary structure, biological potential, and physicochemical, sensory, and allergenic characteristics of the theoretically released antioxidant peptides were predicted in this research. Glycinin and α subunits of β-conglycinin were selected as potential precursors of bioactive peptides based on in silico analysis. The most notable among these are antioxidant peptides. First, the potential of protein precursors for releasing bioactive peptides was evaluated by determining the frequency of occurrence of fragments with a given activity. Through the BIOPEP database analysis, there are several antioxidant bioactive peptides in glycinin and β and α subunits of β-conglycinin sequences. Then, an in silico proteolysis using selected enzymes (papain, bromelain) to obtain antioxidant peptides was investigated and then analyzed using PeptideRanker and Pepcalc. Allergenic analysis using the AllerTop revealed that all in silico proteolysis-derived antioxidant peptides are probably nonallergenic peptides. We also performed molecular docking against MPO (myeloperoxidases) for this peptide. Overall, the present study highlights that glycinin and β and α subunits of β-conglycinin could be promising precursors of bioactive peptides that have an antioxidant peptide for developing several applications.     

In Silico Structure-Based Approach for Group Efficiency Estimation in Fragment-Based Drug Design Using Evaluation of Fragment Contributions

The notion of a contribution of a specific group in an organic molecule’s property and/or activity is both common in our thinking and is still not strictly correct due to the inherent non-additivity of free energy with respect to molecular fragments composing a molecule. The fragment- based drug discovery (FBDD) approach has proven to be fruitful in addressing the above notions. The main difficulty of the FBDD, however, is in its reliance on the low throughput and expensive experimental means of determining the fragment-sized molecules binding. In this article we propose a way to enhance the throughput and availability of the FBDD methods by judiciously using an in silico means of assessing the contribution to ligand-receptor binding energy of fragments of a molecule under question using a previously developed in silico Reverse Fragment Based Drug Discovery (R-FBDD) approach. It has been shown that the proposed structure-based drug discovery (SBDD) type of approach fills in the vacant niche among the existing in silico approaches, which mainly stem from the ligand-based drug discovery (LBDD) counterparts. In order to illustrate the applicability of the approach, our work retrospectively repeats the findings of the use case of an FBDD hit-to-lead project devoted to the experimentally based determination of additive group efficiency (GE)—an analog of ligand efficiency (LE) for a group in the molecule—using the Free-Wilson (FW) decomposition. It is shown that in using our in silico approach to evaluate fragment contributions of a ligand and to estimate GE one can arrive at similar decisions as those made using the experimentally determined activity-based FW decomposition. It is also shown that the approach is rather robust to the choice of the scoring function, provided the latter demonstrates a decent scoring power. We argue that the proposed approach of in silico assessment of GE has a wider applicability domain and expect that it will be widely applicable to enhance the net throughput of drug discovery based on the FBDD paradigm.     

Structure-Based Designing,Solvent Less Synthesis of 1,2,3,4-Tetrahydropyrimidine-5-carboxylate Derivatives: A Combined In Vitro and In Silico Screening Approach

Objective: In this study, small molecules possessing tetrahydropyrimidine derivatives have been synthesized having halogenated benzyl derivatives and carboxylate linkage. As previously reported, FDA approved halogenated pyrimidine derivatives prompted us to synthesize novel compounds in order to evaluate their biological potential. Methodology: Eight pyrimidine derivatives have been synthesized from ethyl acetoacetate, secondary amine, aromatic benzaldehyde by adding catalytic amount of CuCl₂·2H₂O via solvent less Grindstone multicomponent reagent method. Molecular structure reactivity and virtual screening were performed to check their biological efficacy as an anti-oxidant, anti-cancer and anti-diabetic agent. These studies were supported by in vitro analysis and QSAR studies. Results: After combined experimental and virtual screening 5c, 5g and 5e could serve as lead compounds, having low IC₅₀ and high binding affinity.     

Design,Synthesis, In Silico and In Vitro Studies of New Immunomodulatory Anticancer Nicotinamide Derivatives Targeting VEGFR-2

VEGFR-2, the subtype receptor tyrosine kinase (RTK) responsible for angiogenesis, is expressed in various cancer cells. Thus, VEGFER-2 inhibition is an efficient approach for the discovery of new anticancer agents. Accordingly, a new set of nicotinamide derivatives were designed and synthesized to be VEGFR-2 inhibitors. The chemical structures were confirmed using IR, ¹H-NMR, and ¹³C-NMR spectroscopy. The obtained compounds were examined for their anti-proliferative activities against the human cancer cell lines (HCT-116 and HepG2). VEGFR-2 inhibitory activities were determined for the titled compounds. Compound 8 exhibited the strongest anti-proliferative activities with IC₅₀ values of 5.4 and 7.1 µM against HCT-116 and HepG2, respectively. Interestingly, compound 8 was the most potent VEGFR-2 inhibitor with an IC₅₀ value of 77.02 nM (compare to sorafenib: IC₅₀ = 53.65 nM). Treatment of HCT-116 cells with compound 8 produced arrest of the cell cycle at the G0–G1 phase and a total apoptosis increase from 3.05 to 19.82%—6.5-fold in comparison to the negative control. In addition, compound 8 caused significant increases in the expression levels of caspase-8 (9.4-fold) and Bax (9.2-fold), and a significant decrease in the Bcl-2 expression level (3-fold). The effects of compound 8 on the levels of the immunomodulatory proteins (TNF-α and IL-6) were examined. There was a marked decrease in the level of TNF-α (92.37%) compared to the control (82.47%) and a non-significant reduction in the level of IL-6. In silico docking, molecular dynamics simulations, and MM-PBSA studies revealed the high affinity, the correct binding, and the optimum dynamics of compound 8 inside the active site of VEGFR-2. Finally, in silico ADMET and toxicity studies indicated acceptable values of drug-likeness. In conclusion, compound 8 has emerged as a promising anti-proliferative agent targeting VEGFR-2 with significant apoptotic and immunomodulatory effects.     

EBC-232 and 323: A Structural Conundrum Necessitating Unification of Five In Silico Prediction and Elucidation Methods

Structurally unique halimanes EBC-232 and EBC-323, isolated from the Australian rainforest plant Croton insularis, proved considerably difficult to elucidate. The two diastereomers, which consist an unusual oxo-6,7-spiro ring system fused to a dihydrofuran, were solved by unification and consultation of five in silico NMR elucidation and prediction methods [i.e., ACDLabs, olefin strain energy (OSE), DP4, DU8+ and TD DFT CD]. Structure elucidation challenges of this nature are prime test case examples for empowering future AI learning in structure elucidation.     

Synthesis and Rational Design of New Appended 1,2,3-Triazole-uracil Ensembles as Promising Anti-Tumor Agents via In Silico VEGFR-2 Transferase Inhibition

Angiogenesis inhibition is a key step towards the designing of new chemotherapeutic agents. In a view to preparing new molecular entities for cancer treatment, eighteen 1,2,3-triazole-uracil ensembles 5a–r were designed and synthesized via the click reaction. The ligands were well characterized using ¹H-, ¹³C-NMR, elemental analysis and ESI-mass spectrometry. The in silico binding propinquities of the ligands were studied sequentially in the active region of VEGFR-2 using the Molegro virtual docker. All the compounds produced remarkable interactions and potentially inhibitory ligands against VEGFR-2 were obtained with high negative binding energies. Drug-likeness was assessed from the ADME properties. Cytotoxicity of the test compounds was measured against HeLa and HUH-7 tumor cells and NIH/3T3 normal cells by MTT assay. Compound 5h showed higher growth inhibition activity than the positive control, 5-fluorouracil (5-FU), against both HeLa and HUH-7 cells with IC₅₀ values of 4.5 and 7.7 μM respectively. Interestingly, the compounds 5a–r did not show any cytotoxicity towards the normal cell lines. The results advance the position of substituted triazoles in the area of drug design with no ambiguity.     

A Comprehensive In Silico Study of New Metabolites from Heteroxenia fuscescens with SARS-CoV-2 Inhibitory Activity

Chemical investigation of the total extract of the Egyptian soft coral Heteroxenia fuscescens, led to the isolation of eight compounds, including two new metabolites, sesquiterpene fusceterpene A (1) and a sterol fuscesterol A (4), along with six known compounds. The structures of 1–8 were elucidated via intensive studies of their 1D, 2D-NMR, and HR-MS analyses, as well as a comparison of their spectral data with those mentioned in the literature. Subsequent comprehensive in-silico-based investigations against almost all viral proteins, including those of the new variants, e.g., Omicron, revealed the most probable target for these isolated compounds, which was found to be M^pro. Additionally, the dynamic modes of interaction of the putatively active compounds were highlighted, depending on 50-ns-long MDS. In conclusion, the structural information provided in the current investigation highlights the antiviral potential of H. fuscescens metabolites with 3β,5α,6β-trihydroxy steroids with different nuclei against SARS-CoV-2, including newly widespread variants.     

老药新用抗击新冠肺炎*

新冠肺炎疫情爆发以来,临床上通过老药新用的策略发展小分子药物,以用于治疗新冠肺炎。在短时间内迅速从抗病毒、抗炎药物中发现能够用于新冠治疗的药物,如洛匹那韦/利托那韦、磷酸氯喹等。结合几款典型的药物,浅析它们在抗击新冠肺炎中的应用。     

Use of Three‐Dimensional Arterial Models To Predict the In Vivo Behavior of Nanoparticles for Drug Delivery

Nanomaterials have been widely used for applications in biomedical fields and could become indispensable in the near future. However, since it is difficult to optimize in vivo biological behavior in a 3D environment by using a single cell in vitro, there have been many failures in animal models. In vitro prediction systems using 3D human‐tissue models reflecting the 3D location of cell types may be useful to better understand the biological characteristics of nanomaterials for optimization of their function. Herein we demonstrate the potential ability of 3D engineered human‐arterial models for in vitro prediction of the in vivo behavior of nanoparticles for drug delivery. These models enabled optimization of the composition and size of the nanoparticles for targeting and treatment efficacy for atherosclerosis. In vivo experiments with atherosclerotic mice suggested excellent biological characteristics and potential treatment effects of the nanoparticles optimized in vitro.     

层状组装：先进药物控释涂层材料的新选择*

先进的药物控释体系和医用植入体是生物医用材料研究的重要内容,将两者有机结合构成的结合装置为采用药物控释的手段有效解决医用植入体面临的挑战,提升医用植入体的功能提供了新的可能。基于静电交替组装的层层组装技术具有操作简单,涂层组成、厚度可控,适用组装分子和组装基材种类广泛,利于保持药物活性等一系列优点,已成为先进药物控释涂层材料的新选择。本文从层状组装多层膜构建原位药物控释涂层的方法研究,对药物释放的调控和功能药物涂层研究三个方面对这一技术在该领域的应用进行了简要介绍。系统总结了层状组装作为先进药物控释涂层材料的优势。并针对将药物控释与医用植入体有机结合的要求,对现有层状组装涂层方法的不足和今后发展的方向进行了论述。     

Synthesis,In Silico and In Vivo Toxicity Assessment of Functionalized Pyridophenanthridinones via Sequential MW-Assisted Intramolecular Friedel-Crafts Alkylation and Direct C–H Arylation

A rapid, efficient, and original synthesis of novel pyrido[3,2,1-de]phenanthridin-6-ones is reported. First, the key cinnamamide intermediates 8a–f were easily prepared from commercial substituted anilines, cinnamic acid, and 2-bromobenzylbromide in a tandem amidation and N-alkylation protocol. Then, these N-aryl-N-(2-bromobenzyl) cinnamamides 8a–f were subjected to a TFA-mediated intramolecular Friedel-Crafts alkylation followed by a Pd-catalyzed direct C–H arylation to obtain a series of potentially bioactive 4-phenyl-4,5-dihydro-6H,8H-pyrido[3,2,1-de]phenanthridin-6-one derivatives 4a–f in good yields. Finally, the toxicological profile of the prepared final compounds, including their corresponding intermediates, was explored through in silico computational methods, while the acute toxicity toward zebrafish embryos (96 hpf-LC₅₀, 50% lethal concentration) was also determined in the present study.