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.

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 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 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 In Silico Designing of Novel Thiazolidine-2-one Derivatives as Dual PDE4/7 Inhibitors for Inflammatory Disorders

2019 ◽  
Vol 5 (2) ◽  
pp. 149-162
Author(s):  
Ajmer Singh Grewal ◽  
Neelam Sharma ◽  
Sukhbir Singh ◽  
Sandeep Arora
Keyword(s):  
Cyclic Adenosine Monophosphate ◽  
Adenosine Monophosphate ◽  
Docking Study ◽  
Rational Drug Design ◽  
Amino Acid Residues ◽  
Drug Candidates ◽  
Secondary Messenger ◽  
Inflammatory Conditions ◽  
Rational Drug ◽  
Dual Inhibitors

Phosphodiesterase 4 (PDE4) and phosphodiesterase 7 (PDE7), members of PDE super family, catalyse metabolism of secondary messenger cyclic adenosine monophosphate leading to augmented inflammatory processes in pro-inflammatory and immune-modulatory cells. Dual inhibitors of PDE4/7 are a novel class of drug candidates which can regulate pro-inflammatory as well as function of immune T-cell and are particularly beneficial for the treatment of various inflammatory diseasesdevoid of unwanted actions. Intense efforts have been directed towards the development of effective dual inhibitors of both PDE4 and PDE7, but not much success has been reported till yet. The aim of present study was to design some newer substituted thiazolidine-2-one derivatives as dual inhibitors of PDE4/7 using structure based rational drug design approach. A new series of thiazolidine-2-one analogues were designed and molecular docking was performed using AutoDock Vina to explore the bondinginteractions of the designed molecules with the amino acid residues in the active site of target proteins. The docking study indicated that all the substituted thiazolidine-2-one derivatives have appreciable binding interactions with protein residues of both PDE4 and PDE7. The newly designed compounds could be used as lead molecules for development potent and non-toxic dual inhibitors of PDE4/7 for the management of various inflammatory conditions.

scholarly journals Effects of inhibitors on Hsp90’s conformational dynamics, cochaperone and client interactions

2018 ◽  
Author(s):  
Sonja Schmid ◽  
Markus Götz ◽  
Thorsten Hugel
Keyword(s):  
Conformational Dynamics ◽  
Rational Drug Design ◽  
Hsp90 Inhibition ◽  
Allosteric Inhibitors ◽  
Central Target ◽  
Drug Candidates ◽  
Rational Drug ◽  
Kinetic Rate Constants ◽  
Opening And Closing

AbstractThe molecular chaperone and heat-shock protein Hsp90 has become a central target in anti-cancer therapy. Nevertheless, the effect of Hsp90 inhibition is still not understood at the molecular level, preventing a truly rational drug design. Here we report on the effect of the most prominent drug candidates, namely radicicol, geldanamycin, derivatives of purine and novobiocin, on Hsp90’s characteristic conformational dynamics and the binding of three interaction partners. Unexpectedly, the global opening and closing transitions are hardly affected by Hsp90 inhibitors. Instead, the conformational equilibrium, as well as the associated kinetic rate constants remain almost untouched. Moreover, we find no significant changes in the binding of the cochaperones Aha1 and p23 nor of the model substrate Δ131Δ. This holds true for both, competitive and allosteric inhibitors. Therefore, direct inhibition mechanisms, affecting only one molecular interaction, are unlikely. Based on our results, we speculate that the inhibitory action observed in vivo is caused by a combination of subtle effects, which can be used in the search for novel Hsp90 inhibition mechanisms.

An Optimization Algorithm of Foreground Objects Extraction

2011 ◽  
Vol 403-408 ◽  
pp. 169-176
Author(s):  
Xia Yi Zhang ◽  
Zhi Peng Li ◽  
Fu Qiang Liu ◽  
Zhen Jia ◽  
Jian Wei Zhao
Keyword(s):  
Background Subtraction ◽  
Gaussian Mixture Models ◽  
Computational Cost ◽  
Gaussian Mixture ◽  
Object Extraction ◽  
Detection Accuracy ◽  
Foreground Object ◽  
Image Matting ◽  
New Approach ◽  
Novel Approach

In this paper, we propose a novel algorithm for coarse-to-fine foreground objects extraction. There are two general approaches for foreground objects extraction: background subtraction and image matting. Our new approach can not only improve detection accuracy compared with general background subtraction approaches, but also reduce computation burden compared with general image matting approaches. Firstly, we present a novel method called Motion-mask Gaussian Mixture Models (Motion-mask GMMs) to extract coarse foreground regions. This new approach can classify foreground and background pixels more accurately, especially when there are long-time stopping objects in the scene. Secondly, with the coarse foreground regions, we propose a novel approach to make foreground object extraction more accurate based on effective fusion of image registration and image matting. This new method overcomes the template drift problem during template updating and also reduces the expensive computational cost of image matting. Our proposed approach is tested with kinds of video sequences in indoor and outdoor environments. Experimental results demonstrate the accuracy and efficiency of our proposed approach for foreground object extraction.

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.

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