The feasibility of in-silico techniques, together with the computational framework, has been applied to predictive bioremediation aiming to clean-up contaminants, toxicity evaluation, and ...possibilities for the degradation of complex recalcitrant compounds. Emerging contaminants from different industries have posed a significant hazard to the environment and public health. Given current bioremediation strategies, it is often a failure or inadequate for sustainable mitigation of hazardous pollutants. However, clear-cut vital information about biodegradation is quite incomplete from a conventional remediation techniques perspective. Lacking complete information on bio-transformed compounds leads to seeking alternative methods. Only scarce information about the transformed products and toxicity profile is available in the published literature. To fulfill this literature gap, various computational or in-silico technologies have emerged as alternating techniques, which are being recognized as in-silico approaches for bioremediation. Molecular docking, molecular dynamics simulation, and biodegradation pathways predictions are the vital part of predictive biodegradation, including the Quantitative Structure-Activity Relationship (QSAR), Quantitative structure-biodegradation relationship (QSBR) model system. Furthermore, machine learning (ML), artificial neural network (ANN), genetic algorithm (GA) based programs offer simultaneous biodegradation prediction along with toxicity and environmental fate prediction. Herein, we spotlight the feasibility of in-silico remediation approaches for various persistent, recalcitrant contaminants while traditional bioremediation fails to mitigate such pollutants. Such could be addressed by exploiting described model systems and algorithm-based programs. Furthermore, recent advances in QSAR modeling, algorithm, and dedicated biodegradation prediction system have been summarized with unique attributes.
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•Herein, trends in predictive biodegradation to mitigate environmental pollutants are reviewed.•In-silico technologies have emerged as alternating techniques for bioremediation.•Molecular docking, and molecular dynamics simulation are the vital part of predictive biodegradation.•Rule-based pathways prediction systems for predictive biodegradation have been explained with recent updates.•In-silico toxicity prediction as a part of hazard assessment also explained at a glance.
Aptamers are single-stranded DNA or RNA oligonucleotides generated by SELEX that exhibit binding affinity and specificity against a wide variety of target molecules. Compared to RNA aptamers, DNA ...aptamers are much more stable and therefore are widely adopted in a number of applications especially in diagnostics. The tediousness and rigor associated with certain steps of the SELEX intensify the efforts to adopt in silico molecular docking approaches together with in vitro SELEX procedures in developing DNA aptamers. Inspired by these endeavors, we carry out an overview of the in silico molecular docking approaches in DNA aptamer generation, by detailing the stepwise procedures as well as shedding some light on the various softwares used. The in silico maturation strategy and the limitations of the in silico approaches are also underscored.
•We review existing in silico docking approaches in DNA aptamer development.•We review in silico maturation strategy in DNA aptamer development.•We review limitations of the in silico approaches.
The present publication surveys several applications of in silico (i.e., computational) toxicology approaches across different industries and institutions. It highlights the need to develop ...standardized protocols when conducting toxicity-related predictions. This contribution articulates the information needed for protocols to support in silico predictions for major toxicological endpoints of concern (e.g., genetic toxicity, carcinogenicity, acute toxicity, reproductive toxicity, developmental toxicity) across several industries and regulatory bodies. Such novel in silico toxicology (IST) protocols, when fully developed and implemented, will ensure in silico toxicological assessments are performed and evaluated in a consistent, reproducible, and well-documented manner across industries and regulatory bodies to support wider uptake and acceptance of the approaches. The development of IST protocols is an initiative developed through a collaboration among an international consortium to reflect the state-of-the-art in in silico toxicology for hazard identification and characterization. A general outline for describing the development of such protocols is included and it is based on in silico predictions and/or available experimental data for a defined series of relevant toxicological effects or mechanisms. The publication presents a novel approach for determining the reliability of in silico predictions alongside experimental data. In addition, we discuss how to determine the level of confidence in the assessment based on the relevance and reliability of the information.
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To win the battle against resistant, pathogenic bacteria, novel classes of anti-infectives and targets are urgently needed. Bacterial uptake, distribution, metabolic and efflux ...pathways of antibiotics in Gram-negative bacteria determine what we here refer to as bacterial bioavailability. Understanding these mechanisms from a chemical perspective is essential for anti-infective activity and hence, drug discovery as well as drug delivery. A systematic and critical discussion of in bacterio, in vitro and in silico assays reveals that a sufficiently accurate holistic approach is still missing. We expect new findings based on Gram-negative bacterial bioavailability to guide future anti-infective research.
Extraintestinal pathogenic
(ExPEC) is the leading cause in humans of urinary tract infection and bacteremia. The previously published web tool VirulenceFinder ...(http://cge.cbs.dtu.dk/services/VirulenceFinder/) uses whole-genome sequencing (WGS) data for
characterization of
isolates and enables researchers and clinical health personnel to quickly extract and interpret virulence-relevant information from WGS data. In this study, 38 ExPEC-associated virulence genes were added to the existing
VirulenceFinder database. In total, 14,441 alleles were downloaded. A total of 1,890 distinct alleles were added to the database after removal of redundant sequences and analysis of the remaining alleles for open reading frames (ORFs). The database now contains 139 genes-of which 44 are related to ExPEC-and 2,826 corresponding alleles. Construction of the database included validation against 27 primer pairs from previous studies, a search for serotype-specific P fimbriae
alleles, and a BLASTn confirmation of seven genes (
,
,
,
,
,
, and
) not covered by the primers. The augmented database was evaluated using (i) a panel of nine control strains and (ii) 288 human-source
strains classified by PCR as ExPEC and non-ExPEC. We observed very high concordance (average, 93.4%) between PCR and WGS findings, but WGS identified more alleles. In conclusion, the addition of 38 ExPEC-associated genes and the associated alleles to the
VirulenceFinder database allows for a more complete characterization of
isolates based on WGS data, which has become increasingly important considering the plasticity of the
genome.
Different research communities have developed various approaches to assess the credibility of predictive models. Each approach usually works well for a specific type of model, and under some ...epistemic conditions that are normally satisfied within that specific research domain. Some regulatory agencies recently started to consider evidences of safety and efficacy on new medical products obtained using computer modelling and simulation (which is referred to as In Silico Trials); this has raised the attention in the computational medicine research community on the regulatory science aspects of this emerging discipline. But this poses a foundational problem: in the domain of biomedical research the use of computer modelling is relatively recent, without a widely accepted epistemic framing for model credibility. Also, because of the inherent complexity of living organisms, biomedical modellers tend to use a variety of modelling methods, sometimes mixing them in the solution of a single problem. In such context merely adopting credibility approaches developed within other research communities might not be appropriate. In this paper we propose a theoretical framing for assessing the credibility of a predictive models for In Silico Trials, which accounts for the epistemic specificity of this research field and is general enough to be used for different type of models.
The cross-linked enzyme (CLEs) of Thermomyces lanuginosa lipase (TLL) was prepared in an isocyanide-based multi-component reactions (ICMRs) platform by applying three di-acidic cross-linkers to ...unveil more factors contributing to the functional properties of CLEs. The linkers were 1,11-undecanedicarboxylic acid, azelaic acid, and adipic acid with 11, 7, and 4 carbon lengths, respectively, providing a proper tool to investigate the effect of linker length on the activity, stability, and selectivity of the resulting CLEs. The immobilization yields of 60–90 % and the specific activities of 168, 88.4 and 49 U/mg were obtained for the CLEs of 1,11-undecanedicarboxylic acid, azelaic acid, adipic acid, respectively. The lower activity of azelaic and adipic acid-mediated CLEs compared to the soluble TLL (110 U/mg) was explained by in silico calculations. The results revealed that as opposed to 1,11-undecanedicarboxylic acid, both linkers tended to penetrate the enzyme active site, thus resulting in a major inhibitory effect on the enzyme functionality. The thermal and co-solvent stability of the immobilized derivatives improved compared to those of free TLL. The selectivity of CLEs was also examined by catalytic release of main omega-3 fatty acids from fish oil, presenting the highest selectivity of 22 for the CLEs of azelaic acid.
•CLEs of TLL was prepared via a one-step isocyanide-based platform.•Three bifunctional diacid linkers were applied as cross-linking agents.•In silico experiments were conducted to support the results.•High immobilization yields and varied functionality of immobilized TLL were achieved.
•A brief introduction on piperazine derivatives endowed with anticancer activity via green synthetic approach.•Mode of action and SAR study of piperazine analogues as anticancer agents•Eco-friendly ...strategies towards the development of piperazine containing compounds•In-silico design as green approach for piperazine based anticancer therapeutics
Through the exploitation of several conventional strategies in subdisciplines of chemistry and the molecular sciences became challenging due to toxic chemicals in last few years. As a result, there is a growing appreciation towards the newly emerging field of green chemistry which is required as an avenue for sustainable development of heterocyclic derivatives over conventional techniques with improved therapeutic efficacy. Hence, researchers endeavored to adopt environmentally benign green methods for synthesis of piperazine as nitrogen containing heterocyclic derivatives against cancer. With considerable efforts towards green chemistry, this review provides recent insights on several sustainable chemistry dependent synthetic strategies for piperazine analogues with significant inhibition of cancer cells such as, microwave assisted techniques, photoredox catalysis, green solvent, multicomponent single pot reaction and catalyst free synthesis. Accordingly, efforts are continually made by researchers to include these techniques for safe & effective synthetic reactions with the involvement of green solvents and catalysts in order to get product in maximum yield with lesser time consumption. It comprises a 15-year synthetic literature search. The significance of this work lies in its thorough literature review on piperazine containing heterocyclic compounds, and researchers working on the synthesis of piperazines can find a lot of helpful information on environmentally benign synthetic strategies for their development. Additionally, some in-silico based literature has also been cited to inquire the stable interaction between the piperazine structure and several targeted proteins in order to offer insightful information for future anticancer drug development.
A brief introduction on piperazine derivatives endowed with anticancer activity via green chemistry strategies. Display omitted
The idea of a systematic digital representation of the entire known human pathophysiology, which we could call the Virtual Human Twin, has been around for decades. To date, most research groups ...focused instead on developing highly specialised, highly focused patient-specific models able to predict specific quantities of clinical relevance. While it has facilitated harvesting the low-hanging fruits, this narrow focus is, in the long run, leaving some significant challenges that slow the adoption of digital twins in healthcare. This position paper lays the conceptual foundations for developing the Virtual Human Twin (VHT). The VHT is intended as a distributed and collaborative infrastructure, a collection of technologies and resources (data, models) that enable it, and a collection of Standard Operating Procedures (SOP) that regulate its use. The VHT infrastructure aims to facilitate academic researchers, public organisations, and the biomedical industry in developing and validating new digital twins in healthcare solutions with the possibility of integrating multiple resources if required by the specific context of use. Healthcare professionals and patients can also use the VHT infrastructure for clinical decision support or personalised health forecasting. As the European Commission launched the EDITH coordination and support action to develop a roadmap for the development of the Virtual Human Twin, this position paper is intended as a starting point for the consensus process and a call to arms for all stakeholders.
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