scholarly journals Computational Methods of Studying the Binding of Toxins From Venomous Animals to Biological Ion Channels: Theory and Applications

2013 ◽  
Vol 93 (2) ◽  
pp. 767-802 ◽  
Author(s):  
Dan Gordon ◽  
Rong Chen ◽  
Shin-Ho Chung
Keyword(s):  
Ion Channels ◽  
Computational Modeling ◽  
Ion Channel ◽  
Computational Methods ◽  
Structural Information ◽  
Structural Features ◽  
New Drugs ◽  
Computational Techniques ◽  
Theoretical Understanding ◽  
Theoretical Concepts

The discovery of new drugs that selectively block or modulate ion channels has great potential to provide new treatments for a host of conditions. One promising avenue revolves around modifying or mimicking certain naturally occurring ion channel modulator toxins. This strategy appears to offer the prospect of designing drugs that are both potent and specific. The use of computational modeling is crucial to this endeavor, as it has the potential to provide lower cost alternatives for exploring the effects of new compounds on ion channels. In addition, computational modeling can provide structural information and theoretical understanding that is not easily derivable from experimental results. In this review, we look at the theory and computational methods that are applicable to the study of ion channel modulators. The first section provides an introduction to various theoretical concepts, including force-fields and the statistical mechanics of binding. We then look at various computational techniques available to the researcher, including molecular dynamics, Brownian dynamics, and molecular docking systems. The latter section of the review explores applications of these techniques, concentrating on pore blocker and gating modifier toxins of potassium and sodium channels. After first discussing the structural features of these channels, and their modes of block, we provide an in-depth review of past computational work that has been carried out. Finally, we discuss prospects for future developments in the field.

scholarly journals Computational Ion Channel Research: from the Application of Artificial Intelligence to Molecular Dynamics Simulations.

2020 ◽  
Vol 55 (S3) ◽  
pp. 14-45
Keyword(s):  
Artificial Intelligence ◽  
Molecular Dynamics ◽  
Ion Channels ◽  
Ion Channel ◽  
Computational Methods ◽  
Homology Modelling ◽  
Channel Structure ◽  
Learning Approaches ◽  
Qsar Analysis ◽  
Wide Range

Although ion channels are crucial in many physiological processes and constitute an important class of drug targets, much is still unclear about their function and possible malfunctions that lead to diseases. In recent years, computational methods have evolved into important and invaluable approaches for studying ion channels and their functions. This is mainly due to their demanding mechanism of action where a static picture of an ion channel structure is often insufficient to fully understand the underlying mechanism. Therefore, the use of computational methods is as important as chemical-biological based experimental methods for a better understanding of ion channels. This review provides an overview on a variety of computational methods and software specific to the field of ion-channels. Artificial intelligence (or more precisely machine learning) approaches are applied for the sequence-based prediction of ion channel family, or topology of the transmembrane region. In case sufficient data on ion channel modulators is available, these methods can also be applied for quantitative structureactivity relationship (QSAR) analysis. Molecular dynamics (MD) simulations combined with computational molecular design methods such as docking can be used for analysing the function of ion channels including ion conductance, different conformational states, binding sites and ligand interactions, and the influence of mutations on their function. In the absence of a three-dimensional protein structure, homology modelling can be applied to create a model of your ion channel structure of interest. Besides highlighting a wide range of successful applications, we will also provide a basic introduction to the most important computational methods and discuss best practices to get a rough idea of possible applications and risks.

scholarly journals Targeting Trypanothione Reductase, a Key Enzyme in the Redox Trypanosomatid Metabolism, to Develop New Drugs against Leishmaniasis and Trypanosomiases

Molecules ◽  
2020 ◽  
Vol 25 (8) ◽  
pp. 1924 ◽  
Author(s):  
Theo Battista ◽  
Gianni Colotti ◽  
Andrea Ilari ◽  
Annarita Fiorillo
Keyword(s):  
Structural Information ◽  
Redox Homeostasis ◽  
Critical Role ◽  
Structural Features ◽  
Crystallographic Analysis ◽  
New Drugs ◽  
Trypanothione Reductase ◽  
Comprehensive Overview ◽  
Causative Agents ◽  
Key Enzyme

The protozoans Leishmania and Trypanosoma, belonging to the same Trypanosomatidae family, are the causative agents of Leishmaniasis, Chagas disease, and human African trypanosomiasis. Overall, these infections affect millions of people worldwide, posing a serious health issue as well as socio-economical concern. Current treatments are inadequate, mainly due to poor efficacy, toxicity, and emerging resistance; therefore, there is an urgent need for new drugs. Among several molecular targets proposed, trypanothione reductase (TR) is of particular interest for its critical role in controlling the parasite’s redox homeostasis and several classes of active compounds that inhibit TR have been proposed so far. This review provides a comprehensive overview of TR’s structural characterization. In particular, we discuss all the structural features of TR relevant for drug discovery, with a focus on the recent advances made in the understanding of inhibitor binding. The reported cases show how, on the basis of the detailed structural information provided by the crystallographic analysis, it is possible to rationally modify molecular scaffolds to improve their properties.

scholarly journals Exploring ion channel mechanisms : from toxin-based tools to computational methods

2016 ◽  
Author(s):  
◽  
Autoosa Salari
Keyword(s):  
Ion Channels ◽  
Ion Channel ◽  
Building Blocks ◽  
Proper Function ◽  
Computational Techniques ◽  
Pharmacological Agents ◽  
Cellular Excitability ◽  
Basic Functions ◽  
Five Senses ◽  
First Time

Ion channels are the building blocks of cellular excitability, controlling the most basic functions necessary for life to the most complex behaviors. The research presented here addresses questions about the mechanisms by which different ion channels function, as well as, how various toxins from venomous animals can alter ion channel behavior. This was done using a combination of molecular biology, electrophysiology, and computational techniques. The results shed light on the specific structures of a channel required for proper function, and target by pharmacological agents. Importantly, these results have significance in developing animal toxins as research tools and as future therapeutic agents for ion channel associated diseases. Lastly, we demonstrate for the first time, a system to study a protein required for high temperature avoidance in fruit flies. This opens the door to addressing detailed questions about the most poorly understood of the five senses, temperature sensation.

scholarly journals Discovery of New Hits as Antitrypanosomal Agents by In Silico and In Vitro Assays Using Neolignan-Inspired Natural Products from Nectandra leucantha

Molecules ◽  
2021 ◽  
Vol 26 (14) ◽  
pp. 4116
Author(s):  
Sheila C. Araujo ◽  
Fernanda S. Sousa ◽  
Thais A. Costa-Silva ◽  
Andre G. Tempone ◽  
João Henrique G. Lago ◽  
...  
Keyword(s):  
In Silico ◽  
Biological Response ◽  
Structural Features ◽  
New Drugs ◽  
In Vitro Assays ◽  
Computational Techniques ◽  
Phytochemical Study ◽  
Ic50 Value ◽  
In Silico Studies

In the present study, the phytochemical study of the n-hexane extract from flowers of Nectandra leucantha (Lauraceae) afforded six known neolignans (1–6) as well as one new metabolite (7), which were characterized by analysis of NMR, IR, UV, and ESI-HRMS data. The new compound 7 exhibited potent activity against the clinically relevant intracellular forms of T. cruzi (amastigotes), with an IC50 value of 4.3 μM and no observed mammalian cytotoxicity in fibroblasts (CC50 > 200 μM). Based on the results obtained and our previous antitrypanosomal data of 50 natural and semi-synthetic related neolignans, 2D and 3D molecular modeling techniques were employed to help the design of new neolignan-based compounds with higher activity. The results obtained from the models were important to understand the main structural features related to the biological response of the neolignans and to aid in the design of new neolignan-based compounds with better biological activity. Therefore, the results acquired from phytochemical, biological, and in silico studies showed that the integration of experimental and computational techniques consists of a powerful tool for the discovery of new prototypes for development of new drugs to treat CD.

Measurement and Reduction of Radiation Damage in Frozen Hydrated Crystalline Specimens

1978 ◽  
Vol 36 (3) ◽  
pp. 70-77 ◽  
Author(s):  
R.M. Glaeser ◽  
S.B. Hayward
Keyword(s):  
Diffraction Pattern ◽  
Structural Information ◽  
Structural Disorder ◽  
Structural Features ◽  
Biological Macromolecules ◽  
Diffraction Intensity ◽  
Object Structure ◽  
Specimen Material ◽  
Unit Cells ◽  
Identical Unit

Highly ordered or crystalline biological macromolecules become severely damaged and structurally disordered after a brief electron exposure. Evidence that damage and structural disorder are occurring is clearly given by the fading and eventual disappearance of the specimen's electron diffraction pattern. The fading and disappearance of sharp diffraction spots implies a corresponding disappearance of periodic structural features in the specimen. By the same token, there is a oneto- one correspondence between the disappearance of the crystalline diffraction pattern and the disappearance of reproducible structural information that can be observed in the images of identical unit cells of the object structure. The electron exposures that result in a significant decrease in the diffraction intensity will depend somewhat upon the resolution (Bragg spacing) involved, and can vary considerably with the chemical makeup and composition of the specimen material.

HAZARD: An Expert System for Risk Assessment of Environmental Chemicals

1987 ◽  
Vol 26 (01) ◽  
pp. 13-23 ◽  
Author(s):  
H. W. Gottinger
Keyword(s):  
Expert System ◽  
Structural Information ◽  
Chemical Carcinogenesis ◽  
Structural Features ◽  
Environmental Chemicals ◽  
Chemical Carcinogens ◽  
Carcinogenic Activity ◽  
Current State ◽  
Structure Activity ◽  
Carcinogenic Potential

AbstractThe purpose of this paper is to report on an expert system in design that screens for potential hazards from environmental chemicals on the basis of structure-activity relationships in the study of chemical carcinogenesis, particularly with respect to analyzing the current state of known structural information about chemical carcinogens and predicting the possible carcinogenicity of untested chemicals. The structure-activity tree serves as an index of known chemical structure features associated with carcinogenic activity. The basic units of the tree are the principal recognized classes of chemical carcinogens that are subdivided into subclasses known as nodes according to specific structural features that may reflect differences in carcinogenic potential among chemicals in the class. An analysis of a computerized data base of known carcinogens (knowledge base) is proposed using the structure-activity tree in order to test the validity of the tree as a classification scheme (inference engine).

Rapid Online Buffer Exchange: A Method for Screening of Proteins, Protein Complexes, and Cell Lysates by Native Mass Spectrometry

2019 ◽  
Author(s):  
Zachary VanAernum ◽  
Florian Busch ◽  
Benjamin J. Jones ◽  
Mengxuan Jia ◽  
Zibo Chen ◽  
...  
Keyword(s):  
Mass Spectrometry ◽  
High Speed ◽  
Structural Information ◽  
Protein Complexes ◽  
High Sensitivity ◽  
Native Mass Spectrometry ◽  
Structural Features ◽  
Consumer Products ◽  
Cell Lysates ◽  
Protein Expression And Purification

It is important to assess the identity and purity of proteins and protein complexes during and after protein purification to ensure that samples are of sufficient quality for further biochemical and structural characterization, as well as for use in consumer products, chemical processes, and therapeutics. Native mass spectrometry (nMS) has become an important tool in protein analysis due to its ability to retain non-covalent interactions during measurements, making it possible to obtain protein structural information with high sensitivity and at high speed. Interferences from the presence of non-volatiles are typically alleviated by offline buffer exchange, which is timeconsuming and difficult to automate. We provide a protocol for rapid online buffer exchange (OBE) nMS to directly screen structural features of pre-purified proteins, protein complexes, or clarified cell lysates. Information obtained by OBE nMS can be used for fast (<5 min) quality control and can further guide protein expression and purification optimization.

Protein Interaction Domains and Post-Translational Modifications: Structural Features and Drug Discovery Applications

2020 ◽  
Vol 27 (37) ◽  
pp. 6306-6355 ◽  
Author(s):  
Marian Vincenzi ◽  
Flavia Anna Mercurio ◽  
Marilisa Leone
Keyword(s):  
Drug Discovery ◽  
Protein Interaction ◽  
Protein Interactions ◽  
Structural Information ◽  
Protein Complexes ◽  
Structural Features ◽  
Protein Protein Interactions ◽  
Modular Architecture ◽  
Post Translational Modifications ◽  
Interaction Domains

Background:: Many pathways regarding healthy cells and/or linked to diseases onset and progression depend on large assemblies including multi-protein complexes. Protein-protein interactions may occur through a vast array of modules known as protein interaction domains (PIDs). Objective:: This review concerns with PIDs recognizing post-translationally modified peptide sequences and intends to provide the scientific community with state of art knowledge on their 3D structures, binding topologies and potential applications in the drug discovery field. Method:: Several databases, such as the Pfam (Protein family), the SMART (Simple Modular Architecture Research Tool) and the PDB (Protein Data Bank), were searched to look for different domain families and gain structural information on protein complexes in which particular PIDs are involved. Recent literature on PIDs and related drug discovery campaigns was retrieved through Pubmed and analyzed. Results and Conclusion:: PIDs are rather versatile as concerning their binding preferences. Many of them recognize specifically only determined amino acid stretches with post-translational modifications, a few others are able to interact with several post-translationally modified sequences or with unmodified ones. Many PIDs can be linked to different diseases including cancer. The tremendous amount of available structural data led to the structure-based design of several molecules targeting protein-protein interactions mediated by PIDs, including peptides, peptidomimetics and small compounds. More studies are needed to fully role out, among different families, PIDs that can be considered reliable therapeutic targets, however, attacking PIDs rather than catalytic domains of a particular protein may represent a route to obtain selective inhibitors.

A Systematic Review on Popularity, Application and Characteristics of Protein Secondary Structure Prediction Tools

2019 ◽  
Vol 16 (2) ◽  
pp. 159-172 ◽  
Author(s):  
Elaheh Kashani-Amin ◽  
Ozra Tabatabaei-Malazy ◽  
Amirhossein Sakhteman ◽  
Bagher Larijani ◽  
Azadeh Ebrahim-Habibi
Keyword(s):  
Systematic Review ◽  
Secondary Structure ◽  
Structure Prediction ◽  
Web Of Science ◽  
Secondary Structure Prediction ◽  
Structural Information ◽  
Protein Secondary Structure ◽  
Structural Features ◽  
Prediction Tools ◽  
Insight Into

Background: Prediction of proteins’ secondary structure is one of the major steps in the generation of homology models. These models provide structural information which is used to design suitable ligands for potential medicinal targets. However, selecting a proper tool between multiple Secondary Structure Prediction (SSP) options is challenging. The current study is an insight into currently favored methods and tools, within various contexts. Objective: A systematic review was performed for a comprehensive access to recent (2013-2016) studies which used or recommended protein SSP tools. Methods: Three databases, Web of Science, PubMed and Scopus were systematically searched and 99 out of the 209 studies were finally found eligible to extract data. Results: Four categories of applications for 59 retrieved SSP tools were: (I) prediction of structural features of a given sequence, (II) evaluation of a method, (III) providing input for a new SSP method and (IV) integrating an SSP tool as a component for a program. PSIPRED was found to be the most popular tool in all four categories. JPred and tools utilizing PHD (Profile network from HeiDelberg) method occupied second and third places of popularity in categories I and II. JPred was only found in the two first categories, while PHD was present in three fields. Conclusion: This study provides a comprehensive insight into the recent usage of SSP tools which could be helpful for selecting a proper tool.

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