An integrated in silico-in vitro approach for identification of therapeutic drug targets for osteoarthritis

ABSTRACTWithout the availability of disease-modifying drugs, there is an unmet therapeutic need for osteoarthritic patients. During osteoarthritis, the homeostasis of articular chondrocytes is dysregulated and a phenotypical transition called hypertrophy occurs, leading to cartilage degeneration. Targeting this phenotypic transition has emerged as a potential therapeutic strategy. Chondrocyte phenotype maintenance and switch are controlled by an intricate network of intracellular factors, each influenced by a myriad of feedback mechanisms, making it challenging to intuitively predict treatment outcomes. In this study, we developed a regulatory network model using knowledge-based and data-driven modelling technologies. The in silico high-throughput screening of (pairwise) perturbations operated with that network model highlighted conditions impacting the hypertrophic switch. Several combinations were tested in a murine cell line and primary chondrocytes to validate the predicted conditions’ potential. Our in silico-in vitro strategy opens a new route for developing osteoarthritis targeting therapies by refining the early stages of drug discovery.

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Computational and In-Vitro Validation of Natural Molecules as Potential Acetylcholinesterase Inhibitors and Neuroprotective Agents

Current Alzheimer Research ◽

10.2174/1567205016666181212155147 ◽

2019 ◽

Vol 16 (2) ◽

pp. 116-127 ◽

Cited By ~ 2

Author(s):

Ashwani Kumar ◽

Vineet Mehta ◽

Utkarsh Raj ◽

Pritish Kumar Varadwaj ◽

Malairaman Udayabanu ◽

...

Keyword(s):

In Silico ◽

Hippocampal Neurons ◽

Symptomatic Relief ◽

In Vitro Assays ◽

Disease Modifying Drugs ◽

In Silico Docking ◽

Ache Inhibitors ◽

Significant Difference ◽

Disease Modifying

Background: Cholinesterase inhibitors are the first line of therapy for the management of Alzheimer’s disease (AD), however, it is now established that they provide only temporary and symptomatic relief, besides, having several inherited side-effects. Therefore, an alternative drug discovery method is used to identify new and safer ‘disease-modifying drugs’. Methods: Herein, we screened 646 small molecules of natural origin having reported pharmacological and functional values through in-silico docking studies to predict safer neuromodulatory molecules with potential to modulate acetylcholine metabolism. Further, the potential of the predicted molecules to inhibit acetylcholinesterase (AChE) activity and their ability to protect neurons from degeneration was determined through in-vitro assays. Results: Based on in-silico AChE interaction studies, we predicted quercetin, caffeine, ascorbic acid and gallic acid to be potential AChE inhibitors. We confirmed the AChE inhibitory potential of these molecules through in-vitro AChE inhibition assay and compared results with donepezil and begacestat. Herbal molecules significantly inhibited enzyme activity and inhibition for quercetin and caffeine did not show any significant difference from donepezil. Further, the tested molecules did not show any neurotoxicity against primary (E18) hippocampal neurons. We observed that quercetin and caffeine significantly improved neuronal survival and efficiently protected hippocampal neurons from HgCl2 induced neurodegeneration, which other molecules, including donepezil and begacestat, failed to do. Conclusion: Quercetin and caffeine have the potential as “disease-modifying drugs” and may find application in the management of neurological disorders such as AD.

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Phycobilins as Potent Food Bioactive Broad-Spectrum Inhibitors Against Proteases of SARS-CoV-2 and Other Coronaviruses: A Preliminary Study

Frontiers in Microbiology ◽

10.3389/fmicb.2021.645713 ◽

2021 ◽

Vol 12 ◽

Author(s):

Brahmaiah Pendyala ◽

Ankit Patras ◽

Chandravanu Dash

Keyword(s):

Binding Affinity ◽

Broad Spectrum ◽

In Silico ◽

Research Area ◽

Therapeutic Drug ◽

Inhibitor Activity ◽

Current Vaccine ◽

Mutant Strains ◽

The Impact

In the 21st century, we have witnessed three coronavirus outbreaks: SARS in 2003, MERS in 2012, and the ongoing pandemic coronavirus disease 2019 (COVID-19). The search for efficient vaccines and development and repurposing of therapeutic drugs are the major approaches in the COVID-19 pandemic research area. There are concerns about the evolution of mutant strains (e.g., VUI – 202012/01, a mutant coronavirus in the United Kingdom), which can potentially reduce the impact of the current vaccine and therapeutic drug development trials. One promising approach to counter the mutant strains is the “development of effective broad-spectrum antiviral drugs” against coronaviruses. This study scientifically investigates potent food bioactive broad-spectrum antiviral compounds by targeting main protease (Mpro) and papain-like protease (PLpro) proteases of coronaviruses (CoVs) using in silico and in vitro approaches. The results reveal that phycocyanobilin (PCB) shows potential inhibitor activity against both proteases. PCB had the best binding affinity to Mpro and PLpro with IC50 values of 71 and 62 μm, respectively. Also, in silico studies with Mpro and PLpro enzymes of other human and animal CoVs indicate broad-spectrum inhibitor activity of the PCB. As with PCB, other phycobilins, such as phycourobilin (PUB), phycoerythrobilin (PEB), and phycoviolobilin (PVB) show similar binding affinity to SARS-CoV-2 Mpro and PLpro.

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Research fronts of Chemical Biology

Pure and Applied Chemistry ◽

10.1515/pac-2020-1004 ◽

2021 ◽

Vol 0 (0) ◽

Author(s):

Shanshan Lv

Keyword(s):

High Throughput Screening ◽

Drug Targets ◽

Chemical Biology ◽

Rational Design ◽

Future Research ◽

Design Strategies ◽

Binding Assays ◽

Cellular Mechanisms ◽

Diagnostic Technologies

Abstract Over the past decades, researchers have witnessed substantially increasing and ever-growing interests and efforts in Chemical Biology studies, thanks to the development of genome and epi-genome sequencing (revealing potential drug targets), synthetic chemistry (producing new medicines), bioorthogonal chemistry (chemistry in living systems) and high-throughput screening technologies (in vitro cell systems, protein binding assays and phenotypic assays). This report presents literature search results for current research in Chemical Biology, to explore basic principles, summarize recent advances, identify key challenges, and provide suggestions for future research (with a focus on Chemical Biology in the context of human health and diseases). Chemical Biology research can positively contribute to delivering a better understanding of the molecular and cellular mechanisms that accompany pathology underlying diseases, as well as developing improved methods for diagnosis, drug discovery, and therapeutic delivery. While much progress has been made, as shown in this report, there are still further needs and opportunities. For instance, pressing challenges still exist in selecting appropriate targets in biological systems and adopting more rational design strategies for the development of innovative and sustainable diagnostic technologies and medical treatments. Therefore, more than ever, researchers from different disciplines need to collaborate to address the challenges in Chemical Biology.

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Potential Drug Target Identification in Porphyromonas gingivalis using In-silico Subtractive Metabolic Pathway Analysis

Bangladesh Journal of Medical Science ◽

10.3329/bjms.v20i4.54149 ◽

2021 ◽

Vol 20 (4) ◽

pp. 887-896

Author(s):

Prachi Sao ◽

Yamini Chand ◽

Atul Kumar ◽

Sachidanand Singh

Keyword(s):

Porphyromonas Gingivalis ◽

Pathway Analysis ◽

In Silico ◽

Drug Targets ◽

Homo Sapiens ◽

Medical Science ◽

Bone Destruction ◽

Therapeutic Drug ◽

Potential Drug ◽

Narrow Spectrum

Introduction: Porphyromonas Gingivalis (P. gingivalis) a primary periodontal disease pathogen. This bacterium affects sub-gingival tissue and leads to loss of teeth and alveolar bone destruction in the acute stage. In recent years, P. gingivalis is often connected with other diseases such as rheumatoid arthritis, diabetes, Alzheimer’s, and heart disease, though the aetiology is still unclear. Objective: The use of commonly available drugs to treat periodontitis results in various side effects, in particular multi-drug resistant strains. As the development of multidrugresistant strains frequently urges the identification of novel drug targets, the aim of this study is to identify specific targets in the narrow spectrum to combat oral pathogens. Methodology: This study used a comparative and subtractive pathway analysis approach to identify potential drug targets specific to P. gingivalis. Results: The in-silico comparison of the P. gingivalis and Homo sapiens (H. sapiens) metabolic pathways resulted in 13 unique pathogen pathways. A homology search of the 67 enzymes in the unique bacterial pathway using the BLASTp program against the Homo sapiens proteome resulted in fifteen possible targets that are non-homologous to the human proteome. Thirteen genes among 15 potent target encoders are key DEG genes indispensable for P. gingivalis’s survival. A comprehensive analysis of the literature identified three potential therapeutic drug targets. Conclusions: The three most relevant drug targets are Arabinose-5-phosphate isomerase, UDP-2,3-diacylglucosamine hydrolase, and Undecaprenyl diphosphatase. Upon corroboration, these targets may give rise to narrow-spectrum antibiotics that can specificallytreat thedental infection. Bangladesh Journal of Medical Science Vol.20(4) 2021 p.887-896

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Discerning novel drug targets for treating Mycobacterium avium ss. paratuberculosis-associated autoimmune disorders: an in silico approach

Briefings in Bioinformatics ◽

10.1093/bib/bbaa195 ◽

2020 ◽

Author(s):

Anjali Garg ◽

Neelja Singhal ◽

Manish Kumar

Keyword(s):

Multiple Sclerosis ◽

Autoimmune Diseases ◽

Mycobacterium Avium ◽

In Silico ◽

Drug Targets ◽

Molecular Mimicry ◽

Mycobacterium Avium Subspecies Paratuberculosis ◽

In Silico Analysis ◽

Experimental Drugs

Abstract Mycobacterium avium subspecies paratuberculosis (MAP) exhibits ‘molecular mimicry’ with the human host resulting in several autoimmune diseases such as multiple sclerosis, type 1 diabetes mellitus (T1DM), Hashimoto’s thyroiditis, Crohn’s disease (CD), etc. The conventional therapy for autoimmune diseases includes immunosuppressants or immunomodulators that treat the symptoms rather than the etiology and/or causative mechanism(s). Eliminating MAP–the etiopathological agent might be a better strategy to treat MAP-associated autoimmune diseases. In this case study, we conducted a systematic in silico analysis to identify the metabolic chokepoints of MAP’s mimicry proteins and their interacting partners. The probable inhibitors of chokepoint proteins were identified using DrugBank. DrugBank molecules were stringently screened and molecular interactions were analyzed by molecular docking and ‘off-target’ binding. Thus, we identified 18 metabolic chokepoints of MAP mimicry proteins and 13 DrugBank molecules that could inhibit three chokepoint proteins viz. katG, rpoB and narH. On the basis of molecular interaction between drug and target proteins finally eight DrugBank molecules, viz. DB00609, DB00951, DB00615, DB01220, DB08638, DB08226, DB08266 and DB07349 were selected and are proposed for treatment of three MAP-associated autoimmune diseases namely, T1DM, CD and multiple sclerosis. Because these molecules are either approved by the Food and Drug Administration or these are experimental drugs that can be easily incorporated in clinical studies or tested in vitro. The proposed strategy may be used to repurpose drugs to treat autoimmune diseases induced by other pathogens.

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Insights and Perspectives on Emerging Inputs to Weight of Evidence Determinations for Food Safety: Workshop Proceedings

International Journal of Toxicology ◽

10.1177/1091581813508436 ◽

2013 ◽

Vol 32 (6) ◽

pp. 405-414 ◽

Cited By ~ 1

Author(s):

Heidi Bialk ◽

Craig Llewellyn ◽

Alison Kretser ◽

Richard Canady ◽

Richard Lane ◽

...

Keyword(s):

Food Safety ◽

In Silico ◽

High Throughput Screening ◽

Weight Of Evidence ◽

Food Ingredient ◽

Food Ingredients ◽

Safety Assessments ◽

Vitro Data ◽

In Vitro Data

This workshop aimed to elucidate the contribution of computational and emerging in vitro methods to the weight of evidence used by risk assessors in food safety assessments. The following issues were discussed: using in silico and high-throughput screening (HTS) data to confirm the safety of approved food ingredients, applying in silico and HTS data in the process of assessing the safety of a new food ingredient, and utilizing in silico and HTS data in communicating the safety of food ingredients while enhancing the public’s trust in the food supply. Perspectives on integrating computational modeling and HTS assays as well as recommendations for optimizing predictive methods for risk assessment were also provided. Given the need to act quickly or proceed cautiously as new data emerge, this workshop also focused on effectively identifying a path forward in communicating in silico and in vitro data.

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FBDD: In-silico STRATEGY TO INHIBIT MPRO ACTIVITY USING DRUGS FROM PREVIOUS OUTBREAKS

Journal of Experimental Biology and Agricultural Sciences ◽

10.18006/2021.9(4).472.480 ◽

2021 ◽

Vol 9 (4) ◽

pp. 472-480

Author(s):

Gauravi N Trivedi ◽

◽

Janhavi T Karlekar ◽

Khushbu Dhimmar ◽

Hetal kumar Panchal ◽

...

Keyword(s):

Drug Development ◽

In Silico ◽

Drug Targets ◽

Transmission Rate ◽

Respiratory Illness ◽

Primary Treatment ◽

Rational Drug Design ◽

New Drugs ◽

Main Protease

Main protease (Mpro) and Spike (S) proteins are said potential drug targets of COVID-19. Pneumonia like respiratory illness caused by SARS-CoV-2 is spreading rapidly due to its replication and transmission rate. Protease is the protein that is involved in both replication and transcription. Since CoV-2 shares, genomic similarity with CoV and MERS-CoV, drugs from previous outbreaks are used as primary treatment of the disease. In-silico drug development strategies are said to be faster and effective than in-vitro with a lesser amount of risk factors. Fragment Based Drug Designing (FBDD), also known as rational drug design in which a potential target protein is selected and docked with a lead-like molecule that eventually leads to drug development. Nine (9) drugs that are currently being used to treat patients of coronavirus were selected in this study from the latest literature review and fragmented as per rules followed by crosslinking of drug fragments using editor tools. These native drugs and synthesized drugs were then docked against the main protease. Results of the study revealed that one of the crosslinked lead-like compounds showed a higher binding affinity (∆G) more than any of the native compounds. Further, the results of this study suggested that the combination of potential drugs can be an effective way to develop new drugs to treat a deadly disease.

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In Silico Druggability Assessment of the NUDIX Hydrolase Protein Family as a Workflow for Target Prioritization

10.26434/chemrxiv.10026929 ◽

2019 ◽

Author(s):

Maurice Michel ◽

Evert J. Homan ◽

Elisee Wiita ◽

Kia Pedersen ◽

Ingrid Almlöf ◽

...

Keyword(s):

Ligand Binding ◽

In Silico ◽

High Throughput Screening ◽

Drug Targets ◽

Large Scale ◽

Protein Family ◽

Nudix Hydrolase ◽

In Silico Docking ◽

Glide Docking ◽

User Friendly

Computational chemistry has now been widely accepted as a useful tool for shortening lead times in early drug discovery. When selecting new potential drug targets, it is important to assess the likelihood of finding suitable starting points for lead generation before pursuing costly high-throughput screening campaigns. By exploiting available high-resolution crystal structures, an in silico druggability assessment can facilitate the decision of whether, and in cases where several protein family members exist, which of these to pursue experimentally. Many of the algorithms and software suites commonly applied for in silico druggability assessment are complex, technically challenging and not always user-friendly. Here we applied the intuitive open access servers of DoGSite, FTMap and CryptoSite to comprehensively predict ligand binding pockets, druggability scores and conformationally active regions of the NUDIX protein family. In parallel we analyzed potential ligand binding sites, their druggability and hydrophobic-hydrophilic ratio using Schrödinger’s SiteMap. Then an in silico docking cascade of a subset of the ZINC FragNow library using the Glide docking program was performed to assess identified pockets for large-scale small molecule binding. Subsequently, this initial dual ranking of druggable sites within the NUDIX protein family was benchmarked against experimental hit rates obtained both in-house and by others from traditional biochemical and fragment screening campaigns. The observed correlation suggests that the presented user-friendly workflow of a dual parallel in silico druggability assessment is applicable as a standalone method for decision on target prioritization in future screening campaigns. <br>

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In Silico identification of potential drug targets by subtractive genome analysis of Enterococcus faecium DO

10.1101/2020.02.14.948232 ◽

2020 ◽

Author(s):

Marwah Karim ◽

MD Nazrul Islam ◽

G. M. Nurnabi Azad Jewel

Keyword(s):

Alcohol Dehydrogenase ◽

Enterococcus Faecium ◽

In Silico ◽

Drug Targets ◽

3D Structure ◽

Comparative Genomic ◽

Therapeutic Drug ◽

Potential Drug ◽

Novel Drug ◽

Potential Drug Targets

AbstractOnce believed to be a commensal bacteria, Enterococcus faecium has recently emerged as an important nosocomial pathogen worldwide. A recent outbreak of E. faecium unrevealed natural and in vitro resistance against a myriad of antibiotics namely ampicillin, gentamicin and vancomycin due to over-exposure of the pathogen to these antibiotics. This fact combined with the ongoing threat demands the identification of new therapeutic targets to combat E. faecium infections.In this present study, comparative proteome analysis, subtractive genomic approach, metabolic pathway analysis and additional drug prioritizing parameters were used to propose a potential novel drug targets for E. faecium strain DO. Comparative genomic analysis of Kyoto Encyclopedia of Genes and Genomes annotated metabolic pathways identified a total of 207 putative target proteins in E. faecium DO that showed no similarity to human proteins. Among them 105 proteins were identified as essential novel proteins that could serve as potential drug targets through further bioinformatic approaches; such as-prediction of subcellular localization, calculation of molecular weight, and web-based investigation of 3D structural characterization. Eventually 19 non-homologous essential proteins of E. faecium DO were prioritized and proved to have the eligibility to become novel broad-spectrum antibiotic targets. Among these targets aldehyde-alcohol dehydrogenase was found to be involved in maximum pathways, and therefore, was chosen as novel drug target. Interestingly, aldehyde-alcohol dehydrogenase enzyme contains two domains namely acetaldehyde dehydrogenase and alcohol dehydrogenase, on which a 3D structure homology modeling and in silico molecular docking were performed. Finally, eight molecules were confirmed as the most suitable ligands for aldehyde-alcohol dehydrogenase and hence proposed as the potential inhibitors of this target.In conclusion, being human non-homologous, aldehyde-alcohol dehydrogenase protein can be targeted for potential therapeutic drug development in future. However, laboratory based experimental research should be performed to validate our findings in vivo.

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Focus Your Screening Library: Rapid Identification of Novel PDE2 Inhibitors with in silico Driven Library Prioritization and MicroScale Thermophoresis

10.1101/2020.04.22.021360 ◽

2020 ◽

Author(s):

Florian Kaiser ◽

Maximilian G. Plach ◽

Thomas Schubert ◽

V. Joachim Haupt

Keyword(s):

In Silico ◽

High Throughput Screening ◽

Rapid Identification ◽

Chemical Diversity ◽

Chemical Library ◽

Binding Behavior ◽

Microscale Thermophoresis ◽

Excellent Starting Point ◽

Starting Point

Accelerated development of lead structures is of high interest to the pharmaceutical industry in order to decrease development times and costs. We showcase how an intelligent combination of AI-based drug screening with state-of-the-art biophysics drives the rapid identification of novel inhibitor structures with high chemical diversity for cGMP-dependent 3’,5’-cyclic phosphodiesterase (PDE2). The starting point was an off-the-shelve chemical library of two million drug-like compounds. In a single in silico reduction step, we short-listed 125 compounds – the focused library – as potential binders to PDE2 and tested their binding behavior in vitro using MicroScale Thermophoresis (MST). Of this focused library, seven compounds indicated binding to PDE2, translating to a hit rate of 6%. Three of these compounds have affinities in the lower micromolar range. The compound with the highest affinity showed a KD of 10 µM and is thus an excellent starting point for further medicinal chemistry optimization. The results show how innovative and structure-driven in silico approaches and biophysics can be used to accelerate drug discovery and to obtain new molecular scaffolds at a fraction of the costs and time – compared with standard high-throughput screening.

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