Computational methods on food contact chemicals: Big data and in silico screening on nuclear receptors family

Chemosphere ◽  
2021 ◽  
pp. 133422
Author(s):  
Pietro Cozzini ◽  
Francesca Cavaliere ◽  
Giulia Spaggiari ◽  
Gianluca Morelli ◽  
Marco Riani
Keyword(s):  
Big Data ◽  
Nuclear Receptors ◽  
Computational Methods ◽  
In Silico ◽  
In Silico Screening ◽  
Food Contact ◽  
Contact Chemicals

scholarly journals Advancing Computer-Aided Drug Discovery (ACADD): In-Silico Approach towards Nuclear Receptors by Big Data

2021 ◽  
pp. 40-46
Author(s):  
K. Palaniammal ◽  
M. Saravana Roentgen Mani ◽  
R. Mohan Kumar
Keyword(s):  
Big Data ◽  
Biological Activity ◽  
Drug Discovery ◽  
Binding Energy ◽  
Nuclear Receptors ◽  
In Silico ◽  
Structural Parameters ◽  
Receptor Interaction ◽  
Drug Discovery And Development ◽  
Computer Aided

The progression of drug discovery and development is time consuming and costly. Advancing Computer-aided drug discovery (ACADD) is an effective tool in reducing the time and cost of research and development. This study deals with the evaluation of the nuclear receptors for the in-silico biological activity using ligand betulinic acid and dexamethasone. Docking results showed that binding energy was -74.190 kcal/mol when compared with that of the standard (-51.551 kcal/mol). Interaction energy -44.16 & -25.14 kcal/mol) of the ligands also coincide with the binding energy. These ligands have shown the best ligand-receptor interaction based on their structural parameters.

scholarly journals In silico Methods for Identification of Potential Therapeutic Targets

2021 ◽  
Author(s):  
Xuting Zhang ◽  
Fengxu Wu ◽  
Nan Yang ◽  
Xiaohui Zhan ◽  
Jianbo Liao ◽  
...  
Keyword(s):  
Big Data ◽  
Drug Discovery ◽  
Comparative Genomics ◽  
Infectious Diseases ◽  
Computational Methods ◽  
In Silico ◽  
Therapeutic Targets ◽  
Full Potential ◽  
Advantages And Disadvantages ◽  
In Silico Methods

AbstractAt the initial stage of drug discovery, identifying novel targets with maximal efficacy and minimal side effects can improve the success rate and portfolio value of drug discovery projects while simultaneously reducing cycle time and cost. However, harnessing the full potential of big data to narrow the range of plausible targets through existing computational methods remains a key issue in this field. This paper reviews two categories of in silico methods—comparative genomics and network-based methods—for finding potential therapeutic targets among cellular functions based on understanding their related biological processes. In addition to describing the principles, databases, software, and applications, we discuss some recent studies and prospects of the methods. While comparative genomics is mostly applied to infectious diseases, network-based methods can be applied to infectious and non-infectious diseases. Nonetheless, the methods often complement each other in their advantages and disadvantages. The information reported here guides toward improving the application of big data-driven computational methods for therapeutic target discovery. Graphical abstract

Gold-Aptamer-Nanoconstructs Engineered to Detect Conserved Enteroviral Nucleic Acid Sequences

2019 ◽  
Author(s):  
Veeren Chauhan ◽  
Mohamed M Elsutohy ◽  
C Patrick McClure ◽  
Will Irving ◽  
Neil Roddis ◽  
...  
Keyword(s):  
Nucleic Acid ◽  
In Silico ◽  
Point Of Care ◽  
Lateral Flow ◽  
Nucleic Acid Sequence ◽  
In Silico Screening ◽  
Lateral Flow Assays ◽  
Life Threatening ◽  
Software And Hardware ◽  
Nucleic Acid Sequences

<p>Enteroviruses are a ubiquitous mammalian pathogen that can produce mild to life-threatening disease. Bearing this in mind, we have developed a rapid, accurate and economical point-of-care biosensor that can detect a nucleic acid sequences conserved amongst 96% of all known enteroviruses. The biosensor harnesses the physicochemical properties of gold nanoparticles and aptamers to provide colourimetric, spectroscopic and lateral flow-based identification of an exclusive enteroviral RNA sequence (23 bases), which was identified through in silico screening. Aptamers were designed to demonstrate specific complementarity towards the target enteroviral RNA to produce aggregated gold-aptamer nanoconstructs. Conserved target enteroviral nucleic acid sequence (≥ 1x10<sup>-7</sup> M, ≥1.4×10<sup>-14</sup> g/mL), initiates gold-aptamer-nanoconstructs disaggregation and a signal transduction mechanism, producing a colourimetric and spectroscopic blueshift (544 nm (purple) > 524 nm (red)). Furthermore, lateral-flow-assays that utilise gold-aptamer-nanoconstructs were unaffected by contaminating human genomic DNA, demonstrated rapid detection of conserved target enteroviral nucleic acid sequence (< 60 s) and could be interpreted with a bespoke software and hardware electronic interface. We anticipate our methodology will translate in-silico screening of nucleic acid databases to a tangible enteroviral desktop detector, which could be readily translated to related organisms. This will pave-the-way forward in the clinical evaluation of disease and complement existing strategies at overcoming antimicrobial resistance.</p>

Design and in-silico screening of Peptide Nucleic Acid (PNA) inspired novel pronucleotide scaffolds targeting COVID-19

2020 ◽  
Vol 16 ◽  
Author(s):  
Bichismita Sahu ◽  
Santosh Kumar Behera ◽  
Rudradip Das ◽  
Tanay Dalvi ◽  
Arnab Chowdhury ◽  
...  
Keyword(s):  
Nucleic Acid ◽  
In Silico ◽  
Peptide Nucleic Acid ◽  
Large Set ◽  
Nonstructural Proteins ◽  
In Silico Screening ◽  
Replication Process ◽  
Enveloped Virus ◽  
Treatment Regimens ◽  
Novel Coronavirus

Introduction: The outburst of the novel coronavirus COVID-19, at the end of December 2019 has turned itself into a pandemic taking a heavy toll on human lives. The causal agent being SARS-CoV-2, a member of the long-known Coronaviridae family, is a positive sense single-stranded enveloped virus and quite closely related to SARS-CoV. It has become the need of the hour to understand the pathophysiology of this disease, so that drugs, vaccines, treatment regimens and plausible therapeutic agents can be produced. Methods: In this regard, recent studies uncovered the fact that the viral genome of SARS-CoV-2 encodes nonstructural proteins like RNA dependent RNA polymerase (RdRp) which is an important tool for its transcription and replication process. A large number of nucleic acid based anti-viral drugs are being repurposed for treating COVID-19 targeting RdRp. Few of them are in the advanced stage of clinical trials including Remdesivir. While performing close investigation of the large set of nucleic acid based drugs, we were surprised to find that the synthetic nucleic acid backbone is explored very little or rare. Results: We have designed scaffolds derived from peptide nucleic acid (PNA) and subjected them for in-silico screening systematically. These designed molecules have demonstrated excellent binding towards RdRp. Compound 12 was found to possess similar binding affinity as Remdesivir with comparable pharmacokinetics. However, the in-silico toxicity prediction indicates compound 12 may be a superior molecule which can be explored further due to its excellent safety-profile with LD50 (12,000mg/kg) as opposed to Remdesivir (LD50 =1000mg/kg). Conclusion: Compound 12 falls in the safe category of class 6. Synthetic feasibility, equipotent binding and very low toxicity of this peptide nucleic acid derived compounds can serve as a leading scaffold to design, synthesize and evaluate many of similar compounds for the treatment of COVID-19.

In silico screening of pyridoxine carbamates for Anti-Alzheimer’s activities

2020 ◽  
Vol 20 ◽  
Author(s):  
Dnyaneshwar Baswar ◽  
Abha Sharma ◽  
Awanish Mishra
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
In Silico ◽  
Neurodegenerative Disorder ◽  
Biological Activities ◽  
Cholinergic Neurons ◽  
In Silico Screening ◽  
In Silico Studies ◽  
Bbb Permeability ◽  
Ld50 Value

Background: Alzheimer’s disease (AD), an irreversible complex neurodegenerative disorder, is most common type of dementia, with progressive loss of cholinergic neurons. Based on the multi- factorial etiology of Alzheimer’s disease, novel ligands strategy appears as up-coming approach for the development of newer molecules against AD. This study is envisaged to investigate anti-Alzheimer’s potential of 10 synthesized compounds. The screening of compounds (1-10) was carried out using in silico techniques. Methods: For in silico screening of physicochemical properties of compounds molinspiration property engine v.2018.03, Swiss ADME online web-server and pkCSM ADME were used. For pharmacodynamic prediction PASS software while toxicity profile of compounds were analyzed through ProTox-II online software. Simultaneously, molecular docking analysis was performed on mouse AChE enzyme (PDB ID:2JGE, obtained from RSCB PDB) using Auto Dock Tools 1.5.6. Results: Based on in silico studies, compound 9 and 10 have been found to have better drug likeness, LD50 value, and better anti-Alzheimer’s, nootropic activities. However, these compounds had poor blood brain barrier (BBB) permeability. Compound 4 and 9 were predicted with better docking score for AChE enzyme. Conclusion: The outcome of in silico studies have suggested, out of various substitutions at different positions of pyridoxine-carbamate, compound 9 have shown promising drug likeness, with better safety and efficacy profile for anti-Alzheimer’s activity. However, BBB permeability appears as one the major limitation of all these compounds. Further studies are required to confirm its biological activities.

In silico Screening and Molecular Interaction Studies of Tetrahydrocannabinol and its Derivatives with Acetylcholine Binding Protein

2018 ◽  
Vol 12 (2) ◽  
pp. 181-190 ◽  
Author(s):  
Priya P. Panigrahi ◽  
Ramit Singla ◽  
Ankush Bansal ◽  
Moacyr Comar Junior ◽  
Vikas Jaitak ◽  
...  
Keyword(s):  
Molecular Interaction ◽  
In Silico ◽  
Binding Protein ◽  
In Silico Screening ◽  
Acetylcholine Binding Protein ◽  
Interaction Studies

scholarly journals In silico screening of drug candidates for thermoresponsive liposome formulations

2021 ◽  
Author(s):  
Martin Balouch ◽  
Martin Šrejber ◽  
Marek Šoltys ◽  
Petra Janská ◽  
František Štěpánek ◽  
...  
Keyword(s):  
In Silico ◽  
Liposomal Formulation ◽  
In Silico Screening ◽  
Drug Candidates

In silico methodology for compound suitability for liposomal formulation has been developed. Water–lipid partitioning and permeation of candidate compounds from the DrugBank were calculated, and the most appropriate targets validated experimentally.

scholarly journals In Silico Screening of Natural Products Isolated from Mexican Herbal Medicines against COVID-19

Biomolecules ◽  
2021 ◽  
Vol 11 (2) ◽  
pp. 216
Author(s):  
Nadia A. Rivero-Segura ◽  
Juan C. Gomez-Verjan
Keyword(s):  
Natural Products ◽  
In Silico ◽  
Herbal Medicines ◽  
In Silico Screening ◽  
Docking Analysis ◽  
Physiologically Based Pharmacokinetic ◽  
Important Challenge ◽  
Emodin Anthrone ◽  
Therapeutic Tools ◽  
Vaccine Distribution

The COVID-19 pandemic has already taken the lives of more than 2 million people worldwide, causing several political and socio-economic disturbances in our daily life. At the time of publication, there are non-effective pharmacological treatments, and vaccine distribution represents an important challenge for all countries. In this sense, research for novel molecules becomes essential to develop treatments against the SARS-CoV-2 virus. In this context, Mexican natural products have proven to be quite useful for drug development; therefore, in the present study, we perform an in silico screening of 100 compounds isolated from the most commonly used Mexican plants, against the SARS-CoV-2 virus. As results, we identify ten compounds that meet leadlikeness criteria (emodin anthrone, kaempferol, quercetin, aesculin, cichoriin, luteolin, matricin, riolozatrione, monocaffeoyl tartaric acid, aucubin). According to the docking analysis, only three compounds target the key proteins of SARS-CoV-2 (quercetin, riolozatrione and cichoriin), but only one appears to be safe (cichoriin). ADME (absorption, distribution, metabolism and excretion) properties and the physiologically based pharmacokinetic (PBPK) model show that cichoriin reaches higher lung levels (100 mg/Kg, IV); therefore, it may be considered in developing therapeutic tools.

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