Int J Pharm. 2022 Apr 30:121788. doi: 10.1016/j.ijpharm.2022.121788. Online ahead of print.

ABSTRACT

The old alcohol-aversion drug disulfiram (DSF) has aroused wide attention as a drug repurposing strategy in terms of cancer therapy because of the high antitumor efficacy in combination with copper ion. However, numerous defects of DSF (e.g., the short half-life and acid instability) have limited the application in cancer treatment. Cu(DDC)2, the complex of diethyldithiocarbamate (DDC, DSF metabolite) and Cu2+, have been proven as the vital active component on cancer, which have aroused the attention of researchers from DSF to Cu(DDC)2. However, the poor water solubility of Cu(DDC)2 increase more difficulties to the treatment and in-depth investigations of Cu(DDC)2. In this study, sphingomyelin (SM)-based PEGylated liposomes (SM/Chol/DSPE-mPEG2000 (55:40:5, mole%)) were produced as the carriers for Cu(DDC)2 delivery to enhance the water solubility. DDC was added to Cu-containing liposomes with a higher encapsulation efficiency of more than 90%, and it reacted with Cu2+ to synthesize Cu(DDC)2. Due to the high phase transition temperature of SM and strong intermolecular hydrogen bonds with cholesterol, SM-based liposomes would be conducive to enhancing the stability of Cu(DDC)2 and preventing drug leakage during delivery. As proven by pharmacokinetic studies, loading Cu(DDC)2 into liposomes improve bioavailability, and the area under the curve (AUC0-t) and the mean elimination half-life (t1/2) increased 1.9-time and 1.3-time to those of free Cu(DDC)2, respectively. Furthermore, the anticancer effect of Cu(DDC)2 was enhanced by the liposomal encapsulation, thus resulting in remarkable cell apoptosis in vitro and a tumor-inhibiting rate of 77.88% in vivo. Thus, it was concluded that Cu(DDC)2 liposomes could be promising in cancer treatment.

PMID:35504431 | DOI:10.1016/j.ijpharm.2022.121788

Genet Med. 2022 May 2:S1098-3600(22)00718-3. doi: 10.1016/j.gim.2022.04.001. Online ahead of print.

ABSTRACT

PURPOSE: This paper aims to report collective information on safety and efficacy of empagliflozin drug repurposing in individuals with glycogen storage disease type Ib (GSD Ib).

METHODS: This is an international retrospective questionnaire study on the safety and efficacy of empagliflozin use for management of neutropenia/neutrophil dysfunction in patients with GSD Ib, conducted among the respective health care providers from 24 countries across the globe.

RESULTS: Clinical data from 112 individuals with GSD Ib were evaluated, representing a total of 94 treatment years. The median age at start of empagliflozin treatment was 10.5 years (range = 0-38 years). Empagliflozin showed positive effects on all neutrophil dysfunction-related symptoms, including oral and urogenital mucosal lesions, recurrent infections, skin abscesses, inflammatory bowel disease, and anemia. Before initiating empagliflozin, most patients with GSD Ib were on G-CSF (94/112; 84%). At the time of the survey, 49 of 89 (55%) patients previously treated with G-CSF had completely stopped G-CSF, and another 15 (17%) were able to reduce the dose. The most common adverse event during empagliflozin treatment was hypoglycemia, occurring in 18% of individuals.

CONCLUSION: Empagliflozin has a favorable effect on neutropenia/neutrophil dysfunction-related symptoms and safety profile in individuals with GSD Ib.

PMID:35503103 | DOI:10.1016/j.gim.2022.04.001

J Mater Sci. 2022 Apr 27:1-23. doi: 10.1007/s10853-022-07195-8. Online ahead of print.

ABSTRACT

A micro-molecule of dimension 125 nm has caused around 479 million human infections (80 M for the USA) and 6.1 million human deaths (977,000 for the USA) worldwide and slashed the global economy by US$ 8.5 Trillion over two years period. The only other events in recent history that caused comparative human life loss through direct usage (either by human or nature, respectively) of structure-property relations of 'nano-structures' (either human-made or nature, respectively) were nuclear bomb attacks during World War II and 1918 Flu Pandemic. This molecule is called SARS-CoV-2, which causes a disease known as COVID-19. The high liability cost of the pandemic had incentivized various private, government, and academic entities to work towards finding a cure for this and emerging diseases. As an outcome, multiple vaccine candidates are discovered to avoid the infection in the first place. But so far, there has been no success in finding fully effective therapeutic candidates. In this paper, we attempted to provide multiple therapy candidates based upon a sophisticated multi-scale in-silico framework, which increases the probability of the candidates surviving an in-vivo trial. We have selected a group of ligands from the ZINC database based upon previously partially successful candidates, i.e., Hydroxychloroquine, Lopinavir, Remdesivir, Ritonavir. We have used the following robust framework to screen the ligands; Step-I: high throughput molecular docking, Step-II: molecular dynamics analysis, Step-III: density functional theory analysis. In total, we have analyzed 242,000(ligands)*9(proteins) = 2.178 million unique protein binding site/ligand combinations. The proteins were selected based on recent experimental studies evaluating potential inhibitor binding sites. Step-I had filtered that number down to 10 ligands/protein based on molecular docking binding energy, further screening down to 2 ligands/protein based on drug-likeness analysis. Additionally, these two ligands per protein were analyzed in Step-II with a molecular dynamic modeling-based RMSD filter of less than 1Å. It finally suggested three ligands (ZINC001176619532, ZINC000517580540, ZINC000952855827) attacking different binding sites of the same protein(7BV2), which were further analyzed in Step-III to find the rationale behind comparatively higher ligand efficacy.

SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s10853-022-07195-8.

PMID:35502407 | PMC:PMC9045684 | DOI:10.1007/s10853-022-07195-8

EBioMedicine. 2022 Apr 29;80:104038. doi: 10.1016/j.ebiom.2022.104038. Online ahead of print.

ABSTRACT

BACKGROUND: Maintaining a healthy lifestyle to reduce type 2 diabetes (T2D) risk is challenging and additional strategies for T2D prevention are needed. We evaluated several lipid control medications as potential therapeutic options for T2D prevention using tissue-specific predicted gene expression summary statistics in a two-sample Mendelian randomisation (MR) design.

METHODS: Large-scale European genome-wide summary statistics for lipids and T2D were leveraged in our multi-stage analysis to estimate changes in either lipid levels or T2D risk driven by tissue-specific predicted gene expression. We incorporated tissue-specific predicted gene expression summary statistics to proxy therapeutic effects of three lipid control medications [i.e., statins, icosapent ethyl (IPE), and proprotein convertase subtilisin/kexin type-9 inhibitors (PCSK-9i)] on T2D susceptibility using two-sample Mendelian randomisation (MR).

FINDINGS: IPE, as proxied via increased FADS1 expression, was predicted to lower triglycerides and was associated with a 53% reduced risk of T2D. Statins and PCSK-9i, as proxied by reduced HMGCR and PCSK9 expression, respectively, were predicted to lower LDL-C levels but were not associated with T2D susceptibility.

INTERPRETATION: Triglyceride lowering via IPE may reduce the risk of developing T2D in populations of European ancestry. However, experimental validation using animal models is needed to substantiate our results and to motivate randomized control trials (RCTs) for IPE as putative treatment for T2D prevention.

FUNDING: Only summary statistics were used in this analysis. Funding information is detailed under Acknowledgments.

PMID:35500537 | DOI:10.1016/j.ebiom.2022.104038

J Chem Sci (Bangalore). 2022;134(2):57. doi: 10.1007/s12039-022-02046-0. Epub 2022 Apr 22.

ABSTRACT

Exploring the new therapeutic indications of known drugs for treating COVID-19, popularly known as drug repurposing, is emerging as a pragmatic approach especially owing to the mounting pressure to control the pandemic. Targeting multiple targets with a single drug by employing drug repurposing known as the polypharmacology approach may be an optimised strategy for the development of effective therapeutics. In this study, virtual screening has been carried out on seven popular SARS-CoV-2 targets (3CLpro, PLpro, RdRp (NSP12), NSP13, NSP14, NSP15, and NSP16). A total of 4015 approved drugs were screened against these targets. Four drugs namely venetoclax, tirilazad, acetyldigitoxin, and ledipasvir have been selected based on the docking score, ability to interact with four or more targets and having a reasonably good number of interactions with key residues in the targets. The MD simulations and MM-PBSA studies showed reasonable stability of protein-drug complexes and sustainability of key interactions between the drugs with their respective targets throughout the course of MD simulations. The identified four drug molecules were also compared with the known drugs namely elbasvir and nafamostat. While the study has provided a detailed account of the chosen protein-drug complexes, it has explored the nature of seven important targets of SARS-CoV-2 by evaluating the protein-drug complexation process in great detail.

GRAPHICAL ABSTRACT: Drug repurposing strategy against SARS-CoV2 drug targets. Computational analysis was performed to identify repurposable approved drug candidates against SARS-CoV2 using approaches such as virtual screening, molecular dynamics simulation and MM-PBSA calculations. Four drugs namely venetoclax, tirilazad, acetyldigitoxin, and ledipasvir have been selected as potential candidates.

SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s12039-022-02046-0.

PMID:35498548 | PMC:PMC9028909 | DOI:10.1007/s12039-022-02046-0

Front Chem. 2022 Apr 12;10:861209. doi: 10.3389/fchem.2022.861209. eCollection 2022.

ABSTRACT

The COVID-19 pandemic continues unabated, emphasizing the need for additional antiviral treatment options to prevent hospitalization and death of patients infected with SARS-CoV-2. The papain-like protease (PLpro) domain is part of the SARS-CoV-2 non-structural protein (nsp)-3, and represents an essential protease and validated drug target for preventing viral replication. PLpro moonlights as a deubiquitinating (DUB) and deISGylating enzyme, enabling adaptation of a DUB high throughput (HTS) screen to identify PLpro inhibitors. Drug repurposing has been a major focus through the COVID-19 pandemic as it may provide a fast and efficient route for identifying clinic-ready, safe-in-human antivirals. We here report our effort to identify PLpro inhibitors by screening the ReFRAME library of 11,804 compounds, showing that none inhibit PLpro with any reasonable activity or specificity to justify further progression towards the clinic. We also report our latest efforts to improve piperidine-scaffold inhibitors, 5c and 3k, originally developed for SARS-CoV PLpro. We report molecular details of binding and selectivity, as well as in vitro absorption, distribution, metabolism and excretion (ADME) studies of this scaffold. A co-crystal structure of SARS-CoV-2 PLpro bound to inhibitor 3k guides medicinal chemistry efforts to improve binding and ADME characteristics. We arrive at compounds with improved and favorable solubility and stability characteristics that are tested for inhibiting viral replication. Whilst still requiring significant improvement, our optimized small molecule inhibitors of PLpro display decent antiviral activity in an in vitro SARS-CoV-2 infection model, justifying further optimization.

PMID:35494659 | PMC:PMC9039177 | DOI:10.3389/fchem.2022.861209

RSC Adv. 2021 Nov 10;11(57):36181-36198. doi: 10.1039/d1ra05320e. eCollection 2021 Nov 4.

ABSTRACT

Novel coronavirus disease 2019 (COVID-19) has significantly altered the socio-economic status of countries. Although vaccines are now available against the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), a causative agent for COVID-19, it continues to transmit and newer variants of concern have been consistently emerging world-wide. Computational strategies involving drug repurposing offer a viable opportunity to choose a medication from a rundown of affirmed drugs against distinct diseases including COVID-19. While pandemics impede the healthcare systems, drug repurposing or repositioning represents a hopeful approach in which existing drugs can be remodeled and employed to treat newer diseases. In this review, we summarize the diverse computational approaches attempted for developing drugs through drug repurposing or repositioning against COVID-19 and discuss their advantages and limitations. To this end, we have outlined studies that utilized computational techniques such as molecular docking, molecular dynamic simulation, disease-disease association, drug-drug interaction, integrated biological network, artificial intelligence, machine learning and network medicine to accelerate creation of smart and safe drugs against COVID-19.

PMID:35492747 | PMC:PMC9043418 | DOI:10.1039/d1ra05320e

J Biomol Struct Dyn. 2022 May 1:1-16. doi: 10.1080/07391102.2022.2067899. Online ahead of print.

ABSTRACT

Despite substantial progress in surgery, managing multi-tissue injuries is strenuous to accomplish and requires a multi-staged serial treatment of individual tissues. Stimulated regeneration affects the complete structural and functional repair of both hard and soft tissues post-injury and thus serves as an attractive therapeutic option to target multi-tissue injuries. This study utilized data mining and structural analysis to identify a target that has the ability to evoke healing of the two most commonly injured tissues i.e., bone and muscle, and stimulate the inherent vascular connectivity between the tissues. To find out the multipotential molecule the gene expression profile from GSE34747 was extracted and processed to identify the differentially expressed genes (DEGs). The DEGs were then subjected to gene ontology enrichment analysis to filter out a target that is likely to regulate the multi-tissue regeneration. Further, STITCH and PubChem databases were screened to determine a stimulatory drug against the identified target molecule. Finally, the binding affinity and stability of the potential drug candidate(s) against the target were analysed by molecular docking and molecular dynamics simulation. The results revealed that bone morphogenetic protein-4 (BMP-4) was associated with the regulation of the multiple regeneration processes. The computational screening results suggested Retinoic acid and Torularhodin as potential drug candidates for the stimulation of BMP-4. Both drugs demonstrated slightly different but stable interactions with BMP-4, suggesting that the identified drug candidates are likely to serve as potential leads to further enhance tissues regeneration.Communicated by Ramaswamy H. Sarma.

PMID:35491689 | DOI:10.1080/07391102.2022.2067899

Drug Discov Today. 2022 Apr 27:S1359-6446(22)00170-2. doi: 10.1016/j.drudis.2022.04.021. Online ahead of print.

ABSTRACT

Although fungal diseases are a major and growing public health concern, there are only four major classes of drug to treat primary fungal pathogens. The pipeline of new antifungals in clinical development is relatively thin compared with other disease classes. One approach to rapidly identify and provide novel treatment options is to repurpose existing drugs as antifungals. However, such proposed drug-repurposing candidates often suffer suboptimal efficacy and pharmacokinetics (PK) for fungal diseases. Herein, we briefly review the current antifungal drug pipeline and recent approaches to optimize existing drugs into novel molecules with unique modes of action relative to existing antifungal drug classes. Teaser: The use of selective optimization of side activities of repurposed drug candidates has great potential for developing novel antifungal therapies.

PMID:35489676 | DOI:10.1016/j.drudis.2022.04.021

Environ Res. 2022 Apr 26:113282. doi: 10.1016/j.envres.2022.113282. Online ahead of print.

ABSTRACT

A smooth, exceptionally sensitive, correct, and extra reproducible RP-HPLC technique was developed and demonstrated to estimate Sofosbuvir (SOF) in pharmaceutical dosage formulations. This process was carried out by Agilent High-Pressure Liquid Chromatograph 1260 with GI311C Quat. Pump, Phenomenex Luna C-18 (150 mm × 4.6 mm × 5 μm) (USA), and Photodiode Array Detector (PDA) G1315D. The cell section, including acetonitrile and methanol with 80:20 v/v and solution (B) 0.1% phosphoric acid (40:60), was used for the study. However, 10 μL of the sample was injected with a drift flow of 1 mL/min. The separation occurred at a column temperature of 30 °C, and the eluents used PDA set at 260 nm. The retention time of SOF was 5 min. The calibration curve was modified linearly within the range of 0.05-0.15 mg/mL with a correlation coefficient of 0.99 and genuine linear dating among top vicinity and consciousness in the calibration curve. The detection and quantification restrictions were 0.001 and 0.003 mg/mL, respectively. SOF recovery from pharmaceutical components ranged from 98% to 99%. The percentage assay of SOF was 99%. Analytical validation parameters, such as specificity, linearity, precision, accuracy, and selectivity, were studied, and the percentage relative standard deviation (%RSD) was less than 2%. All other key parameters were observed within the desired thresholds. Hence, the proposed RP-HPLC technique was proven effective for developing SOF in bulk and pharmaceutical pill dosage forms. The computational studies and drug repositioning of SOF showed effective antiviral activity and less toxicity based on drug likeness and ADMET profiles.

PMID:35487258 | DOI:10.1016/j.envres.2022.113282

PLoS One. 2022 Apr 28;17(4):e0267677. doi: 10.1371/journal.pone.0267677. eCollection 2022.

ABSTRACT

Morphological changes in the upper airway and the resulting alteration in the nasal respiratory function after jawbone repositioning during orthognathic surgery have garnered attention recently. In particular, nasopharyngeal stenosis, because of the complex influence of both jaws, the effects of which have not yet been clarified owing to postero-superior repositioning of the maxilla, may significantly impact sleep and respiratory function, necessitating further functional evaluation. This study aimed to perform a functional evaluation of the effects of surgery involving maxillary repositioning, which may result in a larger airway resistance if the stenosis worsens the respiratory function, using CFD for treatment planning. A model was developed from CT images obtained preoperatively (PRE) and postoperatively (POST) in females (n = 3) who underwent maxillary postero-superior repositioning using Mimics and ICEM CFD. Simultaneously, a model of stenosis (STENOSIS) was developed by adjusting the severity of stenosis around the PNS to simulate greater repositioning than that in the POST. Inhalation at rest and atmospheric pressure were simulated in each model using Fluent, whereas pressure drop (ΔP) was evaluated using CFD Post. In this study, ΔP was proportional to airway resistance because the flow rate was constant. Therefore, the magnitude of ΔP was evaluated as the level of airway resistance. The ΔP in the airway was lower in the POST compared to the PRE, indicating that the analysis of the effects of repositioning on nasal ventilation showed that current surgery is appropriate with respect to functionality, as it does not compromise respiratory function. The rate of change in the cross-sectional area of the mass extending pharynx (α) was calculated as the ratio of each neighboring section. The closer the α-value is to 1, the smaller the ΔP, so ideally the airway should be constant. This study identified airway shapes that are favorable from the perspective of fluid dynamics.

PMID:35482658 | PMC:PMC9049540 | DOI:10.1371/journal.pone.0267677

Nature. 2022 Apr;604(7907):668-676. doi: 10.1038/s41586-022-04503-9. Epub 2022 Apr 27.

ABSTRACT

As the chemical industry continues to produce considerable quantities of waste chemicals1,2, it is essential to devise 'circular chemistry'3-8 schemes to productively back-convert at least a portion of these unwanted materials into useful products. Despite substantial progress in the degradation of some classes of harmful chemicals9, work on 'closing the circle'-transforming waste substrates into valuable products-remains fragmented and focused on well known areas10-15. Comprehensive analyses of which valuable products are synthesizable from diverse chemical wastes are difficult because even small sets of waste substrates can, within few steps, generate millions of putative products, each synthesizable by multiple routes forming densely connected networks. Tracing all such syntheses and selecting those that also meet criteria of process and 'green' chemistries is, arguably, beyond the cognition of human chemists. Here we show how computers equipped with broad synthetic knowledge can help address this challenge. Using the forward-synthesis Allchemy platform16, we generate giant synthetic networks emanating from approximately 200 waste chemicals recycled on commercial scales, retrieve from these networks tens of thousands of routes leading to approximately 300 important drugs and agrochemicals, and algorithmically rank these syntheses according to the accepted metrics of sustainable chemistry17-19. Several of these routes we validate by experiment, including an industrially realistic demonstration on a 'pharmacy on demand' flow-chemistry platform20. Wide adoption of computerized waste-to-valuable algorithms can accelerate productive reuse of chemicals that would otherwise incur storage or disposal costs, or even pose environmental hazards.

PMID:35478240 | DOI:10.1038/s41586-022-04503-9

Biomed J. 2022 Apr 25:S2319-4170(22)00071-3. doi: 10.1016/j.bj.2022.04.005. Online ahead of print.

ABSTRACT

BACKGROUND: Capmatinib (CAP) is a drug that has been used to treat non-small cell lung cancer (NSCLC) in adults. Presently, its novel effects on skeletal muscle insulin signaling, inflammation, and lipogenesis in adipocytes have been uncovered with a perspective of drug repositioning. However, the impact of CAP on LPS-mediated adhesion between human umbilical vein endothelial cells (HUVECs) and THP-1 monocytes has yet to be investigated.

METHODS: HUVECs and THP-1 monocytes were treated with LPS and CAP. The protein expression levels were determined using Western blotting. Target protein knockdown was conducted using small interfering (si) RNA transfection. Adhesion between HUVECs and THP-1 cells was assayed using green fluorescent dye.

RESULTS: This study found that CAP treatment ameliorated cell adhesion between THP-1 monocytes and HUVECs and the expression of adhesive molecules, such as intracellular adhesion molecule-1 (ICAM-1), vascular cell adhesion molecule-1 (VCAM-1), and E-selectin. Moreover, phosphorylation of inflammatory markers, such as NFκB and IκB as well as TNFα and monocyte chemoattractant protein-1 (MCP-1) released from HUVECs and THP-1 monocytes, was prevented by CAP treatment. Treatment with CAP augmented PPARα and IL-10 expression. siRNA-associated suppression of PPARδ and IL-10 attenuated the effects of CAP on cell adhesion between HUVECs and THP-1 cells and inflammatory responses. Further, PPARα siRNA mitigated CAP-mediated induction of IL-10 expression.

CONCLUSION: These findings imply that CAP improves inflamed endothelial-monocyte adhesion via a PPAR/IL-10-dependent pathway. The current study provides in vitro evidence for a therapeutic approach for treating atherosclerosis.

PMID:35483573 | DOI:10.1016/j.bj.2022.04.005

PLoS Negl Trop Dis. 2022 Apr 28;16(4):e0010291. doi: 10.1371/journal.pntd.0010291. eCollection 2022 Apr.

ABSTRACT

Flaviviruses have caused large epidemics and ongoing outbreaks for centuries. They are now distributed in every continent infecting up to millions of people annually and may emerge to cause future epidemics. Some of the viruses from this group cause severe illnesses ranging from hemorrhagic to neurological manifestations. Despite decades of research, there are currently no approved antiviral drugs against flaviviruses, urging for new strategies and antiviral targets. In recent years, integrated omics data-based drug repurposing paired with novel drug validation methodologies and appropriate animal models has substantially aided in the discovery of new antiviral medicines. Here, we aim to review the latest progress in the development of both new and repurposed (i) direct-acting antivirals; (ii) host-targeting antivirals; and (iii) multitarget antivirals against flaviviruses, which have been evaluated both in vitro and in vivo, with an emphasis on their targets and mechanisms. The search yielded 37 compounds that have been evaluated for their efficacy against flaviviruses in animal models; 20 of them are repurposed drugs, and the majority of them exhibit broad-spectrum antiviral activity. The review also highlighted the major limitations and challenges faced in the current in vitro and in vivo evaluations that hamper the development of successful antiviral drugs for flaviviruses. We provided an analysis of what can be learned from some of the approved antiviral drugs as well as drugs that failed clinical trials. Potent in vitro and in vivo antiviral efficacy alone does not warrant successful antiviral drugs; current gaps in studies need to be addressed to improve efficacy and safety in clinical trials.

PMID:35482672 | DOI:10.1371/journal.pntd.0010291

RSC Adv. 2021 Jul 2;11(38):23450-23458. doi: 10.1039/d1ra03956c. eCollection 2021 Jul 1.

ABSTRACT

The main protease (Mpro or 3CLpro) is a conserved cysteine protease from the coronaviruses and started to be considered an important drug target for developing antivirals, as it produced a deadly outbreak of COVID-19. Herein, we used a combination of drug reposition and computational modeling approaches including molecular docking, molecular dynamics (MD) simulations, and the calculated binding free energy to evaluate a set of drugs in complex with the Mpro enzyme. Particularly, our results show that darunavir and triptorelin drugs have favorable binding free energy (-63.70 and -77.28 kcal mol-1, respectively) in complex with the Mpro enzyme. Based on the results, the structural and energetic features that explain why some drugs can be repositioned to inhibit Mpro from SARS-CoV-2 were exposed. These features should be considered for the design of novel Mpro inhibitors.

PMID:35479789 | PMC:PMC9036595 | DOI:10.1039/d1ra03956c

Front Pharmacol. 2022 Apr 5;13:877401. doi: 10.3389/fphar.2022.877401. eCollection 2022.

NO ABSTRACT

PMID:35479329 | PMC:PMC9037230 | DOI:10.3389/fphar.2022.877401

Bioinform Biol Insights. 2022 Apr 22;16:11779322221090349. doi: 10.1177/11779322221090349. eCollection 2022.

ABSTRACT

Drug discovery (DD) research is a complex field with a high attrition rate. Machine learning (ML) approaches combined to chemoinformatics are of valuable input to this field. We, herein, focused on implementing multiple ML algorithms that shall learn from different molecular fingerprints (FPs) of 65 057 molecules that have been identified as active or inactive against Leishmania major promastigotes. We sought to build a classifier able to predict whether a given molecule has the potential of being anti-leishmanial or not. Using the RDkit library, we calculated 5 molecular FPs of the molecules. Then, we implemented 4 ML algorithms that we trained and tested for their ability to classify the molecules into active/inactive classes based on their chemical structure, encoded by the molecular FPs. Best performers were random forest (RF) and support vector machine (SVM), while atom-pair and topology torsion FPs were the best embedding functions. Both models were further assessed on different stratification levels of the dataset and showed stable performances. At last, we used them to predict the potential of molecules within the Food and Drug Administration (FDA)-approved drugs collection to present anti-Leishmania effects. We ranked these drugs according to their anti-Leishmanial probability and obtained in total seven anti-Leishmania agents, previously described in the literature, within the top 10 of each model. This validates the robustness of the approach, the algorithms, and FPs choices as well as the importance of the dataset size and content. We further engaged these molecules into reverse docking experiments on 3D crystal structures of seven well-studied Leishmania drug targets and could predict the molecular targets for 4 drugs. The results bring novel insights into anti-Leishmania compounds.

PMID:35478992 | PMC:PMC9036323 | DOI:10.1177/11779322221090349

Front Biosci (Landmark Ed). 2022 Apr 1;27(4):113. doi: 10.31083/j.fbl2704113.

ABSTRACT

BACKGROUND: In the current COVID-19 pandemic, with an absence of approved drugs and widely accessible vaccines, repurposing existing drugs is vital to quickly developing a treatment for the disease.

METHODS: In this study, we used a dataset consisting of sequences of viral proteins and chemical structures of pharmaceutical drugs for known drug-target interactions (DTIs) and artificially generated non-interacting DTIs to train a binary classifier with the ability to predict new DTIs. Random Forest (RF), deep neural network (DNN), and convolutional neural networks (CNN) were tested. The CNN and RF models were selected for the classification task.

RESULTS: The models generalized well to the given DTI data and were used to predict DTIs involving SARS-CoV-2 nonstructural proteins (NSPs). We elucidated (with the CNN) 29 drugs involved in 82 DTIs with a 97% probability of interaction, 44 DTIs of which had a 99% probability of interaction, to treat COVID-19. The RF elucidated 6 drugs involved in 17 DTIs with a 90% probability of interacting.

CONCLUSIONS: These results give new insight into possible inhibitors of the viral proteins beyond pharmacophore models and molecular docking procedures used in recent studies.

PMID:35468672 | DOI:10.31083/j.fbl2704113

Front Biosci (Landmark Ed). 2022 Apr 2;27(4):123. doi: 10.31083/j.fbl2704123.

ABSTRACT

COVID-19, caused by the severe acquired respiratory syndrome coronavirus-2 (SARS-CoV-2), is a highly contagious disease that has emerged as a pandemic. Researchers and the medical fraternity are working towards the identification of anti-viral drug candidates. Meanwhile, several alternative treatment approaches are being explored to manage the disease effectively. Various phyto-drugs and essential oils have been reported to have antiviral activity, but this has not been well studied in the context of SARS-CoV-2. The main focus of this review is on the biology of infection and the different therapeutic strategies involved, including drug repurposing and phytopharmaceuticals. The role of phytochemicals in treating COVID-19 and various other diseases has also been emphasized.

PMID:35468682 | DOI:10.31083/j.fbl2704123

J Biomol Struct Dyn. 2022 Apr 25:1-18. doi: 10.1080/07391102.2022.2062787. Online ahead of print.

ABSTRACT

Coronavirus disease 2019 (COVID-19) caused appalling conditions over the globe, which is currently faced by the entire human population. One of the primary reasons behind the uncontrollable situation is the lack of specific therapeutics. In such conditions, drug repurposing of available drugs (viz. Chloroquine, Lopinavir, etc.) has been proposed, but various clinical and preclinical investigations indicated the toxicity and adverse side effects of these drugs. This study explores the inhibition potency of phytochemicals from Tinospora cordifolia (Giloy) against SARS CoV-2 drugable targets (spike glycoprotein and Mpro proteins) using molecular docking and MD simulation studies. ADMET, virtual screening, MD simulation, postsimulation analysis (RMSD, RMSF, Rg, SASA, PCA, FES) and MM-PBSA calculations were carried out to predict the inhibition efficacy of the phytochemicals against SARS CoV-2 targets. Tinospora compounds showed better binding affinity than the corresponding reference. Their binding affinity ranges from -9.63 to -5.68 kcal/mole with spike protein and -10.27 to -7.25 kcal/mole with main protease. Further 100 ns exhaustive simulation studies and MM-PBSA calculations supported favorable and stable binding of them. This work identifies Nine Tinospora compounds as potential inhibitors. Among those, 7-desacetoxy-6,7-dehydrogedunin was found to inhibit both spike (7NEG) and Mpro (7MGS and 6LU7) proteins, and Columbin was found to inhibit selected spike targets (7NEG and 7NX7). In all the analyses, these compounds performed well and confirms the stable binding. Hence the identified compounds, advocated as potential inhibitors can be taken for further in vitro and in vivo experimental validation to determine their anti-SARS-CoV-2 potential.Communicated by Ramaswamy H. Sarma.

PMID:35467486 | DOI:10.1080/07391102.2022.2062787