scholarly journals NICEdrug.ch, a workflow for rational drug design and systems-level analysis of drug metabolism

eLife ◽  
2021 ◽  
Vol 10 ◽  
Author(s):  
Homa MohammadiPeyhani ◽  
Anush Chiappino-Pepe ◽  
Kiandokht Haddadi ◽  
Jasmin Hafner ◽  
Noushin Hadadi ◽  
...  
Keyword(s):  
Drug Targets ◽  
Drug Repurposing ◽  
Rational Drug Design ◽  
Bioactive Molecules ◽  
Lead Discovery ◽  
Minimal Impact ◽  
Practical Applications ◽  
Rational Drug ◽  
Golden Standard ◽  
And Performance

The discovery of a drug requires over a decade of intensive research and financial investments – and still has a high risk of failure. To reduce this burden, we developed the NICEdrug.ch resource, which incorporates 250,000 bioactive molecules, and studied their enzymatic metabolic targets, fate, and toxicity. NICEdrug.ch includes a unique fingerprint that identifies reactive similarities between drug–drug and drug–metabolite pairs. We validated the application, scope, and performance of NICEdrug.ch over similar methods in the field on golden standard datasets describing drugs and metabolites sharing reactivity, drug toxicities, and drug targets. We use NICEdrug.ch to evaluate inhibition and toxicity by the anticancer drug 5-fluorouracil, and suggest avenues to alleviate its side effects. We propose shikimate 3-phosphate for targeting liver-stage malaria with minimal impact on the human host cell. Finally, NICEdrug.ch suggests over 1300 candidate drugs and food molecules to target COVID-19 and explains their inhibitory mechanism for further experimental screening. The NICEdrug.ch database is accessible online to systematically identify the reactivity of small molecules and druggable enzymes with practical applications in lead discovery and drug repurposing.

scholarly journals Rational Drug Design of Antineoplastic Agents Using 3D-QSAR, Cheminformatic, and Virtual Screening Approaches

2019 ◽  
Vol 26 (21) ◽  
pp. 3874-3889 ◽  
Author(s):  
Jelica Vucicevic ◽  
Katarina Nikolic ◽  
John B.O. Mitchell
Keyword(s):  
Virtual Screening ◽  
Drug Design ◽  
Antineoplastic Agents ◽  
Drug Targets ◽  
3D Qsar ◽  
Pharmacophore Modeling ◽  
Rational Drug Design ◽  
Bioactive Molecules ◽  
Computational Approaches ◽  
Rational Drug

Background: Computer-Aided Drug Design has strongly accelerated the development of novel antineoplastic agents by helping in the hit identification, optimization, and evaluation. Results: Computational approaches such as cheminformatic search, virtual screening, pharmacophore modeling, molecular docking and dynamics have been developed and applied to explain the activity of bioactive molecules, design novel agents, increase the success rate of drug research, and decrease the total costs of drug discovery. Similarity, searches and virtual screening are used to identify molecules with an increased probability to interact with drug targets of interest, while the other computational approaches are applied for the design and evaluation of molecules with enhanced activity and improved safety profile. Conclusion: In this review are described the main in silico techniques used in rational drug design of antineoplastic agents and presented optimal combinations of computational methods for design of more efficient antineoplastic drugs.

scholarly journals Database for drug metabolism and comparisons, NICEdrug.ch, aids discovery and design

2020 ◽  
Author(s):  
Homa MohammadiPeyhani ◽  
Anush Chiappino-Pepe ◽  
Kiandokht Haddadi ◽  
Jasmin Hafner ◽  
Noushin Hadadi ◽  
...  
Keyword(s):  
Side Effects ◽  
High Risk ◽  
Small Molecules ◽  
Drug Repurposing ◽  
Lead Discovery ◽  
Liver Stage ◽  
Minimal Impact ◽  
Practical Applications ◽  
Inhibitory Mechanisms ◽  
Financial Investments

AbstractThe discovery of a drug requires over a decade of enormous research and financial investments—and still has a high risk of failure. To reduce this burden, we developed the NICEdrug.ch database, which incorporates 250,000 bio-active molecules, and studied their metabolic targets, fate, and toxicity. NICEdrug.ch includes a unique fingerprint that identifies reactive similarities between drug-drug and drug-metabolite pairs. We use NICEdrug.ch to evaluate inhibition and toxicity by the anticancer drug 5-fluorouracil, and suggest avenues to alleviate its side effects. Clustering based on this fingerprint in statins identified drugs for repurposing. We propose shikimate 3-phosphate for targeting liver-stage malaria with minimal impact on the human host cell. Finally, NICEdrug.ch suggests over 1,300 drugs and food molecules to target COVID-19 and explains their inhibitory mechanisms. The NICEdrug.ch database is accessible online to systematically identify the reactivity of small molecules and druggable enzymes with practical applications in lead discovery and drug repurposing.

Rational Drug Design

2014 ◽  
Vol 4 (1) ◽  
pp. 59-85 ◽  
Author(s):  
Khaled H. Barakat ◽  
Michael Houghton ◽  
D. Lorne Tyrrel ◽  
Jack A. Tuszynski
Keyword(s):  
Drug Design ◽  
Rational Drug Design ◽  
Dimensional Structure ◽  
Computational Tools ◽  
Structure Based Drug Design ◽  
Practical Applications ◽  
3 Dimensional ◽  
Drug Candidates ◽  
The Past ◽  
Rational Drug

For the past three decades rationale drug design (RDD) has been developing as an innovative, rapid and successful way to discover new drug candidates. Many strategies have been followed and several targets with diverse structures and different biological roles have been investigated. Despite the variety of computational tools available, one can broadly divide them into two major classes that can be adopted either separately or in combination. The first class involves structure-based drug design, when the target's 3-dimensional structure is available or it can be computationally generated using homology modeling. On the other hand, when only a set of active molecules is available, and the structure of the target is unknown, ligand-based drug design tools are usually used. This review describes some recent advances in rational drug design, summarizes a number of their practical applications, and discusses both the advantages and shortcomings of the various techniques used.

scholarly journals Fi-score: a novel approach to characterise protein topology and aid in drug discovery studies

2020 ◽  
Author(s):  
Austė Kanapeckaitė ◽  
Claudia Beaurivage ◽  
Matthew Hancock ◽  
Erik Verschueren
Keyword(s):  
Dihedral Angle ◽  
Target Selection ◽  
Gaussian Mixture Models ◽  
Drug Repurposing ◽  
Gaussian Mixture ◽  
Rational Drug Design ◽  
Drug Candidates ◽  
Novel Approach ◽  
Protein Fingerprinting ◽  
Rational Drug

AbstractTarget evaluation is at the centre of rational drug design and biologics development. In order to successfully engineer antibodies, T-cell receptors or small molecules it is necessary to identify and characterise potential binding or contact sites on therapeutically relevant target proteins. Currently, there are numerous challenges in achieving a better docking precision as well as characterising relevant sites. We devised a first-of-its-kind in silico protein fingerprinting approach based on dihedral angle and B-factor distribution to probe binding sites and sites of structural importance. In addition, we showed that the entire protein regions or individual structural subsets can be profiled using our derived fi-score based on amino acid dihedral angle and B-factor distribution. We further described a method to assess the structural profile and extract information on sites of importance using machine learning Gaussian mixture models. In combination, these biophysical analytical methods could potentially help to classify and systematically analyse not only targets but also drug candidates that bind to specific sites which would greatly improve pre-screening stage, target selection and drug repurposing efforts in finding other matching targets.

Computational and Pharmacogenomic Insights on Hypertension Treatment: Rational Drug Design and Optimization Strategies

2019 ◽  
Vol 21 (1) ◽  
pp. 18-33 ◽  
Author(s):  
Lakshmanan Loganathan ◽  
Krishnasamy Gopinath ◽  
Vadivel Murugan Sankaranarayanan ◽  
Ritushree Kukreti ◽  
Kannan Rajendran ◽  
...  
Keyword(s):  
Drug Design ◽  
Drug Targets ◽  
Antihypertensive Drugs ◽  
Rational Drug Design ◽  
Hypertension Treatment ◽  
Genetic Traits ◽  
Drug Responses ◽  
Computational Screening ◽  
Rational Drug ◽  
Multiple Drugs

Background:: Hypertension is a prevalent cardiovascular complication caused by genetic and nongenetic factors. Blood pressure (BP) management is difficult because most patients become resistant to monotherapy soon after treatment initiation. Although many antihypertensive drugs are available, some patients do not respond to multiple drugs. Identification of personalized antihypertensive treatments is a key for better BP management. Objective:: This review aimed to elucidate aspects of rational drug design and other methods to develop better hypertension management. Results:: Among hypertension-related signaling mechanisms, the renin-angiotensin-aldosterone system is the leading genetic target for hypertension treatment. Identifying a single drug that acts on multiple targets is an emerging strategy for hypertension treatment, and could be achieved by discovering new drug targets with less mutated and highly conserved regions. Extending pharmacogenomics research to include patients with hypertension receiving multiple antihypertensive drugs could help identify the genetic markers of hypertension. However, available evidence on the role of pharmacogenomics in hypertension is limited and primarily focused on candidate genes. Studies on hypertension pharmacogenomics aim to identify the genetic causes of response variations to antihypertensive drugs. Genetic association studies have identified single nucleotide polymorphisms affecting drug responses. To understand how genetic traits alter drug responses, computational screening of mutagenesis can be utilized to observe drug response variations at the protein level, which can help identify new inhibitors and drug targets to manage hypertension. Conclusions:: Rational drug design facilitates the discovery and design of potent inhibitors. However, further research and clinical validation are required before novel inhibitors can be clinically used as antihypertensive therapies.

scholarly journals Binding site matching in rational drug design: algorithms and applications

2018 ◽  
Vol 20 (6) ◽  
pp. 2167-2184 ◽  
Author(s):  
Misagh Naderi ◽  
Jeffrey Mitchell Lemoine ◽  
Rajiv Gandhi Govindaraj ◽  
Omar Zade Kana ◽  
Wei Pan Feinstein ◽  
...  
Keyword(s):  
Small Molecules ◽  
Binding Site ◽  
Protein Structures ◽  
Chemical Properties ◽  
Drug Repurposing ◽  
Rational Drug Design ◽  
Basic Knowledge ◽  
Rational Drug ◽  
Binding Pockets ◽  
Local Protein

Abstract Interactions between proteins and small molecules are critical for biological functions. These interactions often occur in small cavities within protein structures, known as ligand-binding pockets. Understanding the physicochemical qualities of binding pockets is essential to improve not only our basic knowledge of biological systems, but also drug development procedures. In order to quantify similarities among pockets in terms of their geometries and chemical properties, either bound ligands can be compared to one another or binding sites can be matched directly. Both perspectives routinely take advantage of computational methods including various techniques to represent and compare small molecules as well as local protein structures. In this review, we survey 12 tools widely used to match pockets. These methods are divided into five categories based on the algorithm implemented to construct binding-site alignments. In addition to the comprehensive analysis of their algorithms, test sets and the performance of each method are described. We also discuss general pharmacological applications of computational pocket matching in drug repurposing, polypharmacology and side effects. Reflecting on the importance of these techniques in drug discovery, in the end, we elaborate on the development of more accurate meta-predictors, the incorporation of protein flexibility and the integration of powerful artificial intelligence technologies such as deep learning.

scholarly journals Rational Drug Design Rational Drug Design

2017 ◽  
pp. 1144-1174
Author(s):  
Khaled H. Barakat ◽  
Michael Houghton ◽  
D. Lorne Tyrrel ◽  
Jack A. Tuszynski
Keyword(s):  
Drug Design ◽  
Rational Drug Design ◽  
The Other ◽  
Dimensional Structure ◽  
Design Tools ◽  
Structure Based Drug Design ◽  
Practical Applications ◽  
3 Dimensional ◽  
Drug Candidates ◽  
Rational Drug

For the past three decades rationale drug design (RDD) has been developing as an innovative, rapid and successful way to discover new drug candidates. Many strategies have been followed and several targets with diverse structures and different biological roles have been investigated. Despite the variety of computational tools available, one can broadly divide them into two major classes that can be adopted either separately or in combination. The first class involves structure-based drug design, when the target's 3-dimensional structure is available or it can be computationally generated using homology modeling. On the other hand, when only a set of active molecules is available, and the structure of the target is unknown, ligand-based drug design tools are usually used. This review describes some recent advances in rational drug design, summarizes a number of their practical applications, and discusses both the advantages and shortcomings of the various techniques used.

scholarly journals Evaluation of Virtual Screening Strategies for the Identification of γ-Secretase Inhibitors and Modulators

Molecules ◽  
2021 ◽  
Vol 27 (1) ◽  
pp. 176
Author(s):  
Alicia Ioppolo ◽  
Melissa Eccles ◽  
David Groth ◽  
Giuseppe Verdile ◽  
Mark Agostino
Keyword(s):  
Small Molecules ◽  
Rational Drug Design ◽  
Bioactive Molecules ◽  
Cell Physiology ◽  
Rational Drug ◽  
Screening Strategies ◽  
Selective Agents ◽  
Progression Of Disease ◽  
Insight Into ◽  
Screening Approaches

γ-Secretase is an intramembrane aspartyl protease that is important in regulating normal cell physiology via cleavage of over 100 transmembrane proteins, including Amyloid Precursor Protein (APP) and Notch family receptors. However, aberrant proteolysis of substrates has implications in the progression of disease pathologies, including Alzheimer’s disease (AD), cancers, and skin disorders. While several γ-secretase inhibitors have been identified, there has been toxicity observed in clinical trials associated with non-selective enzyme inhibition. To address this, γ-secretase modulators have been identified and pursued as more selective agents. Recent structural evidence has provided an insight into how γ-secretase inhibitors and modulators are recognized by γ-secretase, providing a platform for rational drug design targeting this protease. In this study, docking- and pharmacophore-based screening approaches were evaluated for their ability to identify, from libraries of known inhibitors and modulators with decoys with similar physicochemical properties, γ-secretase inhibitors and modulators. Using these libraries, we defined strategies for identifying both γ-secretase inhibitors and modulators incorporating an initial pharmacophore-based screen followed by a docking-based screen, with each strategy employing distinct γ-secretase structures. Furthermore, known γ-secretase inhibitors and modulators were able to be identified from an external set of bioactive molecules following application of the derived screening strategies. The approaches described herein will inform the discovery of novel small molecules targeting γ-secretase.

scholarly journals Computational Repurposing Model of Curcumin as a Drug

2021 ◽  
Vol 68 (1) ◽  
Author(s):  
Ratna Roy ◽  
Ratul Bhowmik ◽  
Shatarupa Seth ◽  
Snigdha Bhattacharyya ◽  
Sounok Sengupta
Keyword(s):  
Viral Infections ◽  
Drug Repurposing ◽  
Viral Disease ◽  
Global Scale ◽  
Rational Drug Design ◽  
Viral Diseases ◽  
The Novel ◽  
Viral Pathogens ◽  
Positive Effects ◽  
Rational Drug

Viral diseases continue to be a public threat on a global scale day by day and the world is in a continuing battle with the novel deadly viral Diseases and with no prompt medicines accessible the scourge brought about by the disease is expanding step by step. The ongoing need to develop new antiviral drugs with fewer side-effects and that are effective against viral pathogens has spurred the research community to invest in various drug discovery strategies, one of which is drug repurposing the methods of finding most promising existing compounds which has able to give best positive effects against viral infections. We present a docking?based screening using a quantum mechanical scoring of drug Curcumin with Proteins with PDB id’s 4B3V, 5LK0, 6BM8, 4QUZ, 6SJV, 1JLF, 5EG7, 7K40 could display antiviral activity against Rubella, Hanta, Herpes, Noro, papilloma, HIV, Influenza, COVID19. Clearly, these compounds should be further evaluated in experimental assays and clinical trials to confirm their actual activity against the viral disease. We hope that repurposing of the drug from our recommendation may contribute to the rational drug design against the above viruses.

scholarly journals DRUG REPURPOSING FOR MALARIA AND DENGUE USING COMPUTATIONAL MODELLING.

2020 ◽  
Vol 4 (11) ◽  
Author(s):  
Prajakta Velankar ◽  
Sara Rehman ◽  
Yukti Thakkar
Keyword(s):  
Clinical Trials ◽  
Drug Design ◽  
Antiviral Activity ◽  
Computational Modelling ◽  
Drug Repurposing ◽  
Rational Drug Design ◽  
Quantum Mechanical ◽  
Rational Drug ◽  
The World ◽  
Approved Drugs

By and by the world is in a battle with the diseases like Malaria and Dengue with no prompt medicines accessible the scourge brought about by the Malaria and Dengue is expanding step by step. A ton of researchers are continuing for the potential medication up-and-comer that could help the medical care framework in this battle. We present a docking?based screening using a quantum mechanical scoring of a library built from approved drugs ie Remdesivir, Hydroxy-chloroquine, Curcumin, Moroxydine, Artesunate Sulphate, Mefloquine, Doxycycline, Atovaquone, Indinavir, and compounds that are with Malaria and Dengue Mpro Proteins could display antiviral activity against these diseases. Clearly, these compounds should be further evaluated in experimental assays and clinical trials to confirm their actual activity against the disease. We hope that these findings may contribute to the rational drug design against Malaria and Dengue Keywords: Malaria, Dengue, Drug Repurposings, Computer Aid Drug Design, In silico drug development

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