scholarly journals Artificial Intelligence (AI) Tools Constructed via the 5-Steps Rule for Predicting Post-Translational Modifications

2019 ◽  
Vol 3 (1) ◽  
Author(s):  
Chou Kuo-Chen
Keyword(s):  
Artificial Intelligence ◽  
Post Translational Modifications

scholarly journals De Novo Design of New Chemical Entities (NCEs) for SARS-CoV-2 Using Artificial Intelligence

2020 ◽  
Author(s):  
Navneet Bung ◽  
Sowmya Ramaswamy Krishnan ◽  
Gopalakrishnan Bulusu ◽  
Arijit Roy
Keyword(s):  
Artificial Intelligence ◽  
Small Molecules ◽  
De Novo ◽  
Chemical Space ◽  
De Novo Design ◽  
Protein Targets ◽  
Post Translational Modifications ◽  
Global Pandemic ◽  
New Chemical Entities ◽  
3Cl Protease

The novel SARS-CoV-2 is the source of a global pandemic COVID-19, which has severely affected the health and economy of several countries. Multiple studies are in progress, employing diverse approaches to design novel therapeutics against the potential target proteins in SARS-CoV-2. One of the well-studied protein targets for coronaviruses is the chymotrypsin-like (3CL) protease, responsible for post-translational modifications of viral polyproteins essential for its survival and replication in the host. There are ongoing attempts to repurpose the existing viral protease inhibitors against 3CL protease of SARS-CoV-2. Recent studies have proven the efficiency of artificial intelligence techniques in learning the known chemical space and generating novel small molecules. In this study, we employed deep neural network-based generative and predictive models for de novo design of new small molecules capable of inhibiting the 3CL protease. The generated small molecules were filtered and screened against the binding site of the 3CL protease structure of SARS-CoV-2. Based on the screening results and further analysis, we have identified 31 potential compounds as ideal candidates for further synthesis and testing against SARS-CoV-2. The generated small molecules were also compared with available natural products. Two of the generated small molecules showed high similarity to a plant natural product, Aurantiamide, which can be used for rapid testing during this time of crisis.

scholarly journals De Novo Design of New Chemical Entities (NCEs) for SARS-CoV-2 Using Artificial Intelligence

2020 ◽  
Author(s):  
Navneet Bung ◽  
Sowmya Ramaswamy Krishnan ◽  
Gopalakrishnan Bulusu ◽  
Arijit Roy
Keyword(s):  
Artificial Intelligence ◽  
Small Molecules ◽  
De Novo ◽  
Chemical Space ◽  
De Novo Design ◽  
Protein Targets ◽  
Post Translational Modifications ◽  
Global Pandemic ◽  
New Chemical Entities ◽  
3Cl Protease

The novel SARS-CoV-2 is the source of a global pandemic COVID-19, which has severely affected the health and economy of several countries. Multiple studies are in progress, employing diverse approaches to design novel therapeutics against the potential target proteins in SARS-CoV-2. One of the well-studied protein targets for coronaviruses is the chymotrypsin-like (3CL) protease, responsible for post-translational modifications of viral polyproteins essential for its survival and replication in the host. There are ongoing attempts to repurpose the existing viral protease inhibitors against 3CL protease of SARS-CoV-2. Recent studies have proven the efficiency of artificial intelligence techniques in learning the known chemical space and generating novel small molecules. In this study, we employed deep neural network-based generative and predictive models for de novo design of new small molecules capable of inhibiting the 3CL protease. The generated small molecules were filtered and screened against the binding site of the 3CL protease structure of SARS-CoV-2. Based on the screening results and further analysis, we have identified 31 potential compounds as ideal candidates for further synthesis and testing against SARS-CoV-2. The generated small molecules were also compared with available natural products. Two of the generated small molecules showed high similarity to a plant natural product, Aurantiamide, which can be used for rapid testing during this time of crisis.

scholarly journals De Novo Design of New Chemical Entities (NCEs) for SARS-CoV-2 Using Artificial Intelligence

2020 ◽  
Author(s):  
Navneet Bung ◽  
Sowmya Ramaswamy Krishnan ◽  
Gopalakrishnan Bulusu ◽  
Arijit Roy
Keyword(s):  
Artificial Intelligence ◽  
Small Molecules ◽  
De Novo ◽  
Chemical Space ◽  
De Novo Design ◽  
Protein Targets ◽  
Post Translational Modifications ◽  
Global Pandemic ◽  
New Chemical Entities ◽  
3Cl Protease

The novel SARS-CoV-2 is the source of a global pandemic COVID-19, which has severely affected the health and economy of several countries. Multiple studies are in progress, employing diverse approaches to design novel therapeutics against the potential target proteins in SARS-CoV-2. One of the well-studied protein targets for coronaviruses is the chymotrypsin-like (3CL) protease, responsible for post-translational modifications of viral<br>polyproteins essential for its survival and replication in the host. There are ongoing attempts to repurpose the existing viral protease inhibitors against 3CL protease of SARS-<br>CoV-2. Recent studies have proven the efficiency of artificial intelligence techniques in learning the known chemical space and generating novel small molecules. In this study,<br>we employed deep neural network-based generative and predictive models for de novo design of new small molecules capable of inhibiting the 3CL protease. The generated<br>small molecules were filtered and screened against the binding site of the 3CL protease structure of SARS-CoV-2. Based on the screening results and further analysis, we have<br>identified 31 potential compounds as ideal candidates for further synthesis and testing against SARS-CoV-2.

Protein Engineering for Improved Health: Technological Perspectives

2019 ◽  
Vol 20 (9) ◽  
pp. 856-860 ◽  
Author(s):  
Mandeep ◽  
Rajeshwari Sinha ◽  
Pratyoosh Shukla
Keyword(s):  
Artificial Intelligence ◽  
Protein Engineering ◽  
Disease Diagnosis ◽  
Future Research ◽  
The Novel ◽  
Post Translational Modifications ◽  
Novel Proteins ◽  
The World ◽  
Health Related ◽  
Research Endeavor

Protein engineering has enabled development of novel proteins aimed at disease diagnosis, alleviation and improved health attributes. The present article provides an overview of recent approaches and techniques used to modify proteins at diverse levels, which find therapeutically relevant applications. There is immense interest among researchers to discover new and increasingly valuable solutions for various health related issues and protein engineering could be a possible venue to sort out such problems. In this mini review we have tried to decipher some of the novel aspects of protein engineering in terms of protein-based therapeutics and diagnostics, in-silico tools and related approaches. A special emphasis has been given for some innovative aspects of protein-nanoparticle conjugates; use of artificial intelligence (AI)- based tools and post-translational modifications. Utilization of such approaches in protein engineering might be ground breaking in future research endeavor of researchers across the world.

Reading the phosphorylation code: binding of the 14-3-3 protein to multivalent client phosphoproteins

2020 ◽  
Vol 477 (7) ◽  
pp. 1219-1225 ◽  
Author(s):  
Nikolai N. Sluchanko
Keyword(s):  
Protein Function ◽  
Intrinsically Disordered Protein ◽  
Structural Basis ◽  
Major Protein ◽  
Post Translational Modifications ◽  
Protein Protein Interaction ◽  
Intrinsically Disordered ◽  
Biochemical Journal ◽  
Multiple Binding ◽  
And Control

Many major protein–protein interaction networks are maintained by ‘hub’ proteins with multiple binding partners, where interactions are often facilitated by intrinsically disordered protein regions that undergo post-translational modifications, such as phosphorylation. Phosphorylation can directly affect protein function and control recognition by proteins that ‘read’ the phosphorylation code, re-wiring the interactome. The eukaryotic 14-3-3 proteins recognizing multiple phosphoproteins nicely exemplify these concepts. Although recent studies established the biochemical and structural basis for the interaction of the 14-3-3 dimers with several phosphorylated clients, understanding their assembly with partners phosphorylated at multiple sites represents a challenge. Suboptimal sequence context around the phosphorylated residue may reduce binding affinity, resulting in quantitative differences for distinct phosphorylation sites, making hierarchy and priority in their binding rather uncertain. Recently, Stevers et al. [Biochemical Journal (2017) 474: 1273–1287] undertook a remarkable attempt to untangle the mechanism of 14-3-3 dimer binding to leucine-rich repeat kinase 2 (LRRK2) that contains multiple candidate 14-3-3-binding sites and is mutated in Parkinson's disease. By using the protein-peptide binding approach, the authors systematically analyzed affinities for a set of LRRK2 phosphopeptides, alone or in combination, to a 14-3-3 protein and determined crystal structures for 14-3-3 complexes with selected phosphopeptides. This study addresses a long-standing question in the 14-3-3 biology, unearthing a range of important details that are relevant for understanding binding mechanisms of other polyvalent proteins.

Dicarbonyl derived post-translational modifications: chemistry bridging biology and aging-related disease

2020 ◽  
Vol 64 (1) ◽  
pp. 97-110
Author(s):  
Christian Sibbersen ◽  
Mogens Johannsen
Keyword(s):  
Mass Spectrometry ◽  
Future Research ◽  
Amino Acid Residues ◽  
Post Translational Modification ◽  
Dicarbonyl Compounds ◽  
Protein Targets ◽  
Post Translational Modifications ◽  
Reactive Protein ◽  
Glycation End Products ◽  
Direct Mass Spectrometry

Abstract In living systems, nucleophilic amino acid residues are prone to non-enzymatic post-translational modification by electrophiles. α-Dicarbonyl compounds are a special type of electrophiles that can react irreversibly with lysine, arginine, and cysteine residues via complex mechanisms to form post-translational modifications known as advanced glycation end-products (AGEs). Glyoxal, methylglyoxal, and 3-deoxyglucosone are the major endogenous dicarbonyls, with methylglyoxal being the most well-studied. There are several routes that lead to the formation of dicarbonyl compounds, most originating from glucose and glucose metabolism, such as the non-enzymatic decomposition of glycolytic intermediates and fructosyl amines. Although dicarbonyls are removed continuously mainly via the glyoxalase system, several conditions lead to an increase in dicarbonyl concentration and thereby AGE formation. AGEs have been implicated in diabetes and aging-related diseases, and for this reason the elucidation of their structure as well as protein targets is of great interest. Though the dicarbonyls and reactive protein side chains are of relatively simple nature, the structures of the adducts as well as their mechanism of formation are not that trivial. Furthermore, detection of sites of modification can be demanding and current best practices rely on either direct mass spectrometry or various methods of enrichment based on antibodies or click chemistry followed by mass spectrometry. Future research into the structure of these adducts and protein targets of dicarbonyl compounds may improve the understanding of how the mechanisms of diabetes and aging-related physiological damage occur.

The challenge of detecting modifications on proteins

2020 ◽  
Vol 64 (1) ◽  
pp. 135-153 ◽  
Author(s):  
Lauren Elizabeth Smith ◽  
Adelina Rogowska-Wrzesinska
Keyword(s):  
Mass Spectrometry ◽  
Protein Function ◽  
Chemical Properties ◽  
Lysine Acetylation ◽  
Mass Determination ◽  
Post Translational Modifications ◽  
Site Specific ◽  
The Common

Abstract Post-translational modifications (PTMs) are integral to the regulation of protein function, characterising their role in this process is vital to understanding how cells work in both healthy and diseased states. Mass spectrometry (MS) facilitates the mass determination and sequencing of peptides, and thereby also the detection of site-specific PTMs. However, numerous challenges in this field continue to persist. The diverse chemical properties, low abundance, labile nature and instability of many PTMs, in combination with the more practical issues of compatibility with MS and bioinformatics challenges, contribute to the arduous nature of their analysis. In this review, we present an overview of the established MS-based approaches for analysing PTMs and the common complications associated with their investigation, including examples of specific challenges focusing on phosphorylation, lysine acetylation and redox modifications.

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