Computer-Assisted Drug Virtual Screening Based on the Natural Product Databases

2019 ◽  
Vol 20 (4) ◽  
pp. 293-301 ◽  
Author(s):  
Baoyu Yang ◽  
Jing Mao ◽  
Bing Gao ◽  
Xiuli Lu

Background:Computer-assisted drug virtual screening models the process of drug screening through computer simulation technology, by docking small molecules in some of the databases to a certain protein target. There are many kinds of small molecules databases available for drug screening, including natural product databases.Methods:Plants have been used as a source of medication for millennia. About 80% of drugs were either natural products or related analogues by 1990, and many natural products are biologically active and have favorable absorption, distribution, metabolization, excretion, and toxicology.Results:In this paper, we review the natural product databases’ contributions to drug discovery based on virtual screening, focusing particularly on the introductions of plant natural products, microorganism natural product, Traditional Chinese medicine databases, as well as natural product toxicity prediction databases.Conclusion:We highlight the applications of these databases in many fields of virtual screening, and attempt to forecast the importance of the natural product database in next-generation drug discovery.

2019 ◽  
Vol 4 (6) ◽  
Author(s):  
Eleni Koulouridi ◽  
Marilia Valli ◽  
Fidele Ntie-Kang ◽  
Vanderlan da Silva Bolzani

Abstract Databases play an important role in various computational techniques, including virtual screening (VS) and molecular modeling in general. These collections of molecules can contain a large amount of information, making them suitable for several drug discovery applications. For example, vendor, bioactivity data or target type can be found when searching a database. The introduction of these data resources and their characteristics is used for the design of an experiment. The description of the construction of a database can also be a good advisor for the creation of a new one. There are free available databases and commercial virtual libraries of molecules. Furthermore, a computational chemist can find databases for a general purpose or a specific subset such as natural products (NPs). In this chapter, NP database resources are presented, along with some guidelines when preparing an NP database for drug discovery purposes.


2021 ◽  
Author(s):  
Giang Nguyen ◽  
Jack Bennett ◽  
Sherrie Liu ◽  
Sarah Hancock ◽  
Daniel Winter ◽  
...  

The structural diversity of natural products offers unique opportunities for drug discovery, but challenges associated with their isolation and screening can hinder the identification of drug-like molecules from complex natural product extracts. Here we introduce a mass spectrometry-based approach that integrates untargeted metabolomics with multistage, high-resolution native mass spectrometry to rapidly identify natural products that bind to therapeutically relevant protein targets. By directly screening crude natural product extracts containing thousands of drug-like small molecules using a single, rapid measurement, novel natural product ligands of human drug targets could be identified without fractionation. This method should significantly increase the efficiency of target-based natural product drug discovery workflows.


2014 ◽  
Vol 3 (1) ◽  
pp. 1 ◽  
Author(s):  
Geoffrey A. Cordell

“Why didn’t they develop natural product drugs in a sustainable manner at the beginning of this century?”  In 2035, when about 10.0 billion will inhabit Earth, will this be our legacy as the world contemplates the costs and availability of synthetic and gene-based products for primary health care?  Acknowledging the recent history of the relationship between humankind and the Earth, it is essential that the health care issues being left for our descendants be considered in terms of resources. For most people in the world, there are two vast health care “gaps”, access to quality drugs and the development of drugs for major global and local diseases.  Consequently for all of these people, plants, in their various forms, remain a primary source of health care.  In the developed countries, natural products derived from plants assume a relatively minor role in health care, as prescription and over-the-counter products, even with the widespread use of phytotherapeutical preparations.  Significantly, pharmaceutical companies have retrenched substantially in their disease areas of focus.  These research areas do not include the prevalent diseases of the middle- and lower-income countries, and important diseases of the developed world, such as drug resistance. What then is the vision for natural product research to maintain the choices of drug discovery and pharmaceutical development for future generations?  In this discussion some facets of how natural products must be involved globally, in a sustainable manner, for improving health care will be examined within the framework of the new term “ecopharmacognosy”, which invokes sustainability as the basis for research on biologically active natural products.  Access to the biome, the acquisition, analysis and dissemination of plant knowledge, natural product structure diversification, biotechnology development, strategies for natural product drug discovery, and aspects of multitarget therapy and synergy research will be discussed.  Options for the future will be presented which may be significant as countries decide how to develop approaches to relieve their own disease burden, and the needs of their population for improved access to medicinal agents.


2021 ◽  
Author(s):  
Giang Nguyen ◽  
Jack Bennett ◽  
Sherrie Liu ◽  
Sarah Hancock ◽  
Daniel Winter ◽  
...  

The structural diversity of natural products offers unique opportunities for drug discovery, but challenges associated with their isolation and screening can hinder the identification of drug-like molecules from complex natural product extracts. Here we introduce a mass spectrometry-based approach that integrates untargeted metabolomics with multistage, high-resolution native mass spectrometry to rapidly identify natural products that bind to therapeutically relevant protein targets. By directly screening crude natural product extracts containing thousands of drug-like small molecules using a single, rapid measurement, novel natural product ligands of human drug targets could be identified without fractionation. This method should significantly increase the efficiency of target-based natural product drug discovery workflows.


2020 ◽  
Vol 56 (15) ◽  
pp. 2280-2283 ◽  
Author(s):  
Abigail R. Hanby ◽  
Nikolaj S. Troelsen ◽  
Thomas J. Osberger ◽  
Sarah L. Kidd ◽  
Kim T. Mortensen ◽  
...  

Herein, we describe the natural product inspired synthesis of 38 complex small molecules based upon 20 unique frameworks suitable for fragment-based screening.


2020 ◽  
Vol 36 (10) ◽  
pp. 3266-3267
Author(s):  
Claudio Mirabello ◽  
Björn Wallner

Abstract Motivation In the past few years, drug discovery processes have been relying more and more on computational methods to sift out the most promising molecules before time and resources are spent to test them in experimental settings. Whenever the protein target of a given disease is not known, it becomes fundamental to have accurate methods for ligand-based virtual screening, which compares known active molecules against vast libraries of candidate compounds. Recently, 3D-based similarity methods have been developed that are capable of scaffold hopping and to superimpose matching molecules. Results Here, we present InterLig, a new method for the comparison and superposition of small molecules using topologically independent alignments of atoms. We test InterLig on a standard benchmark and show that it compares favorably to the best currently available 3D methods. Availability and implementation The program is available from http://wallnerlab.org/InterLig. Supplementary information Supplementary data are available at Bioinformatics online.


2019 ◽  
Author(s):  
Claudio Mirabello ◽  
Björn Wallner

AbstractIn the past few years, drug discovery processes have been relying more and more on computational methods to sift out the most promising molecules before time and resources are spent to test them in experimental settings. Whenever the protein target of a given disease is not known, it becomes fundamental to have accurate methods for ligand-based Virtual Screening, which compare known active molecules against vast libraries of candidate compounds. Recently, 3D-based similarity methods have been developed that are capable of scaffold-hopping and to superimpose matching molecules. Here, we present InterLig, a new method for the comparison and superposition of small molecules based on 3D, topologically-independent alignments of atoms. We test InterLig on a standard benchmark and show that it compares favorably to the best currently available 3D methods.InterLig is open source and is available to everyone at: http://wallnerlab.org/interlig.


2020 ◽  
Vol 17 (2) ◽  
pp. 82-90 ◽  
Author(s):  
Ghodsi Mohammadi Ziarani ◽  
Fatemeh Mohajer ◽  
Zohreh kheilkordi

Background: Natural products have been received attention due to their importance in human life as those are biologically active. In this review, there are some reports through different methods related to the synthesis of the indolizidine 195B which was extracted from poisonous frog; however, due to respect nature, the synthesis of natural compounds such as indolizidine has been attracted much attention among scientists and researchers. Objective: This review discloses the procedures and methods to provide indolizidine 195B from 1989 to 2018 due to their importance as a natural product. Conclusion: There are several methods to give rise to the indolizidine 195B as a natural product that is highly active from the biological perspective in pharmaceutical chemistry. In summary, many protocols for the preparations of indolizidine 195B from various substrates, several reagents, and conditions have been reported from different aromatic and aliphatic.


BioChem ◽  
2021 ◽  
Vol 1 (1) ◽  
pp. 36-48
Author(s):  
Ivan Jacobs ◽  
Manolis Maragoudakis

Computer-assisted de novo design of natural product mimetics offers a viable strategy to reduce synthetic efforts and obtain natural-product-inspired bioactive small molecules, but suffers from several limitations. Deep learning techniques can help address these shortcomings. We propose the generation of synthetic molecule structures that optimizes the binding affinity to a target. To achieve this, we leverage important advancements in deep learning. Our approach generalizes to systems beyond the source system and achieves the generation of complete structures that optimize the binding to a target unseen during training. Translating the input sub-systems into the latent space permits the ability to search for similar structures, and the sampling from the latent space for generation.


Molecules ◽  
2022 ◽  
Vol 27 (2) ◽  
pp. 349
Author(s):  
Asim Najmi ◽  
Sadique A. Javed ◽  
Mohammed Al Bratty ◽  
Hassan A. Alhazmi

Natural products represents an important source of new lead compounds in drug discovery research. Several drugs currently used as therapeutic agents have been developed from natural sources; plant sources are specifically important. In the past few decades, pharmaceutical companies demonstrated insignificant attention towards natural product drug discovery, mainly due to its intrinsic complexity. Recently, technological advancements greatly helped to address the challenges and resulted in the revived scientific interest in drug discovery from natural sources. This review provides a comprehensive overview of various approaches used in the selection, authentication, extraction/isolation, biological screening, and analogue development through the application of modern drug-development principles of plant-based natural products. Main focus is given to the bioactivity-guided fractionation approach along with associated challenges and major advancements. A brief outline of historical development in natural product drug discovery and a snapshot of the prominent natural drugs developed in the last few decades are also presented. The researcher’s opinions indicated that an integrated interdisciplinary approach utilizing technological advances is necessary for the successful development of natural products. These involve the application of efficient selection method, well-designed extraction/isolation procedure, advanced structure elucidation techniques, and bioassays with a high-throughput capacity to establish druggability and patentability of phyto-compounds. A number of modern approaches including molecular modeling, virtual screening, natural product library, and database mining are being used for improving natural product drug discovery research. Renewed scientific interest and recent research trends in natural product drug discovery clearly indicated that natural products will play important role in the future development of new therapeutic drugs and it is also anticipated that efficient application of new approaches will further improve the drug discovery campaign.


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