Medicinal Plants and Their Role in Inflammation: A Close Look on Future Drug Discovery

Parasitic diseases continue represent a threat on a global scale, particularly among the poorest countries in the world. This is particularly because of the absence of vaccines, and in some cases, resistance against available drugs, currently being used for their treatment. In this review emphasis is laid on natural products and scaffolds from African medicinal plants (AMPs) for lead drug discovery and possible further development of drugs for the treatment of parasitic diseases. In the discussion, emphasis has been laid on alkaloids, terpenoids, quinones, flavonoids and narrower compound classes of compounds with micromolar range activities against Schistosoma, Trypanosoma and Leishmania species. Suggestions for future drug development from African medicinal plants have also been provided.

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Arrayed CRISPR reveals genetic regulators of tau aggregation, autophagy and mitochondria in Alzheimer’s disease model

Scientific Reports ◽

10.1038/s41598-021-82658-7 ◽

2021 ◽

Vol 11 (1) ◽

Cited By ~ 1

Author(s):

Lishu Duan ◽

Mufeng Hu ◽

Joseph A. Tamm ◽

Yelena Y. Grinberg ◽

Fang Shen ◽

...

Keyword(s):

Alzheimer’S Disease ◽

Alzheimer's Disease ◽

Drug Discovery ◽

Disease Model ◽

Mitochondrial Morphology ◽

Individual Gene ◽

Human Genes ◽

Future Drug ◽

Tau Aggregation

AbstractAlzheimer’s disease (AD) is a common neurodegenerative disease with poor prognosis. New options for drug discovery targets are needed. We developed an imaging based arrayed CRISPR method to interrogate the human genome for modulation of in vitro correlates of AD features, and used this to assess 1525 human genes related to tau aggregation, autophagy and mitochondria. This work revealed (I) a network of tau aggregation modulators including the NF-κB pathway and inflammatory signaling, (II) a correlation between mitochondrial morphology, respiratory function and transcriptomics, (III) machine learning predicted novel roles of genes and pathways in autophagic processes and (IV) individual gene function inferences and interactions among biological processes via multi-feature clustering. These studies provide a platform to interrogate underexplored aspects of AD biology and offer several specific hypotheses for future drug discovery efforts.

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Structural Basis of SARS-CoV-2 3CLpro and Anti-COVID-19 Drug Discovery from Medicinal Plants

10.20944/preprints202002.0193.v1 ◽

2020 ◽

Cited By ~ 6

Author(s):

Muhammad Tahir ul Qamar ◽

Safar M. Alqahtani ◽

Mubarak A. Alamri ◽

Ling-Ling Chen

Keyword(s):

Life Cycle ◽

Drug Discovery ◽

Medicinal Plants ◽

Severe Acute Respiratory Syndrome ◽

Medicinal Plant ◽

Homology Model ◽

Structural Basis ◽

Health Concerns ◽

Recent Outbreak ◽

Drug Discovery Target

The recent outbreak of coronavirus disease 2019 (COVID-19) caused by SARS-CoV-2 in December 2019 raised global health concerns. The viral 3-chymotrypsin-like cysteine protease (3CLpro) enzyme, which controls coronavirus replication and is essential for its life cycle, is a proven drug discovery target in the case of severe acute respiratory syndrome coronavirus (SARS-CoV) and middle east respiratory syndrome coronavirus (MERS-CoV). Recent studies revealed that the genome sequence of SARS-CoV-2 is very similar to that of SARS-CoV. Therefore, herein, we analysed the 3CLpro sequence, constructed a 3D homology model, and screened it against a medicinal plant library containing 32,297 potential anti-viral phytochemicals/traditional Chinese medicinal compounds. Our analyses revealed that the top nine hits may serve as potential anti- SARS-CoV-2 lead molecules for further optimisation and drug development to control COVID-19.

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COMPUTATIONAL APPROACHES FOR DRUG DISCOVERY FROM MEDICINAL PLANTS IN THE ERA OF DATA DRIVEN RESEARCH

INDIAN DRUGS ◽

10.53879/id.58.08.12930 ◽

2021 ◽

Vol 58 (08) ◽

pp. 7-23

Author(s):

Pratibha Pansari ◽

Keyword(s):

Drug Discovery ◽

Medicinal Plants ◽

In Silico ◽

Drug Target ◽

Target Gene ◽

Scientific Work ◽

Data Driven ◽

Network Pharmacology ◽

Gene Pathway ◽

Topological Network

The significant scientific work on the development of bio-active compound databases, computational technologies, and the integration of Information Technology with Biotechnology has brought a revolution in the domain of drug discovery. These tools facilitate the medicinal plant-based in silico drug discovery, which has become the frontier of pharmacological science. In this review article, we elucidate the methodology of in silico drug discovery for the medicinal plants and present an outlook on recent tools and technologies. Further, we explore the multi-component, multi-target, and multi-pathway mechanism of the bio-active compounds with the help of Network Pharmacology, which enables us to create a topological network between drug, target, gene, pathway, and disease.

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A new platform for drug discovery

Future Drug Discovery ◽

10.4155/fdd-2019-0030 ◽

2019 ◽

Vol 1 (2) ◽

pp. FDD20

Author(s):

Tuomas PJ Knowles

Keyword(s):

Drug Discovery ◽

Protein Analysis ◽

Harvard University ◽

Next Generation ◽

Biotech Company ◽

University Of Cambridge ◽

Future Drug ◽

The University ◽

Scientific Officer

Professor Tuomas Knowles gained his PhD in biophysics from the University of Cambridge (UK) in 2007 and went on to work at Harvard University (MA, USA) before returning to Cambridge as a lecturer, gaining professorship in 2015. He is the founder and Chief Scientific Officer of Fluidic Analytics (Cambridge, UK), a biotech company developing next-generation protein analysis platforms that operate under native conditions in solution. Here he speaks to Future Drug Discovery Editor Jennifer Straiton about Fluidic Analytics' new platform Fluidity One-W, discussing how it works and what benefit it can bring to the field of drug discovery.

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