Covid 19 – Structural proteins and prospective drug candidates (Preprint)

2020 ◽  
Author(s):  
A.N Anoopkumar ◽  
Sharrel Rebello ◽  
Embalil Mathachan Aneesh
Keyword(s):  
Causative Agent ◽  
Protein Level ◽  
Drug Targets ◽  
Current Paper ◽  
Structural Proteins ◽  
Drug Candidates ◽  
Propagation Properties

UNSTRUCTURED Covid 19 the causative agent of the current devastating pandemic has turned out to be a notorious virus to all men-irrespective of either common to scientific calibre. Attempts to combat this deadly virus are the need of the hour and quite often the best way to defeat an opponent is to keenly study about its structural and propagation properties. The current paper describes briefly Covid 19 at the genomic, structural and protein level to the best of our knowledge. Furthermore, the prospects of possible drug targets that could aid in the control of this virus are also discussed.

Dengue Structural Proteins as Antiviral Drug Targets: Current Status in the Drug Discovery & Development

2021 ◽  
pp. 113527
Author(s):  
Akshatha H. S ◽  
Gurubasavaraj V. Pujar ◽  
Arun Kumar Sethu ◽  
Meduri Bhagyalalitha ◽  
Manisha Singh
Keyword(s):  
Drug Discovery ◽  
Drug Targets ◽  
Antiviral Drug ◽  
Structural Proteins ◽  
Current Status

scholarly journals Endoplasmic Reticulum Stress Regulators: New Drug Targets for Parkinson’s Disease

2021 ◽  
pp. 1-10
Author(s):  
Vera Kovaleva ◽  
Mart Saarma
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Endoplasmic Reticulum ◽  
Protein Folding ◽  
Er Stress ◽  
Protein Misfolding ◽  
Drug Targets ◽  
Dopamine Neurons ◽  
Drug Candidates ◽  
The Unfolded Protein Response

Parkinson’s disease (PD) pathology involves progressive degeneration and death of vulnerable dopamine neurons in the substantia nigra. Extensive axonal arborisation and distinct functions make this type of neurons particularly sensitive to homeostatic perturbations, such as protein misfolding and Ca2 + dysregulation. Endoplasmic reticulum (ER) is a cell compartment orchestrating protein synthesis and folding, as well as synthesis of lipids and maintenance of Ca2 +-homeostasis in eukaryotic cells. When misfolded proteins start to accumulate in ER lumen the unfolded protein response (UPR) is activated. UPR is an adaptive signalling machinery aimed at relieving of protein folding load in the ER. When UPR is chronic, it can either boost neurodegeneration and apoptosis or cause neuronal dysfunctions. We have recently discovered that mesencephalic astrocyte-derived neurotrophic factor (MANF) exerts its prosurvival action in dopamine neurons and in animal model of PD through the direct binding to UPR sensor inositol-requiring protein 1 alpha (IRE1α) and attenuation of UPR. In line with this, UPR targeting resulted in neuroprotection and neurorestoration in various preclinical PD animal models. Therefore, growth factors (GFs), possessing both neurorestorative activity and restoration of protein folding capacity are attractive as drug candidates for PD treatment especially their blood-brain barrier penetrating analogs and small molecule mimetics. In this review, we discuss ER stress as a therapeutic target to treat PD; we summarize the existing preclinical data on the regulation of ER stress for PD treatment. In addition, we point out the crucial aspects for successful clinical translation of UPR-regulating GFs and new prospective in GFs-based treatments of PD, focusing on ER stress regulation.

Developing novel chemical entities for the treatment of lysosomal storage disorders: an academic perspective

2015 ◽  
Vol 309 (12) ◽  
pp. F996-F999 ◽  
Author(s):  
James A. Shayman
Keyword(s):  
Drug Targets ◽  
Lysosomal Storage ◽  
Federal Drug Administration ◽  
Drug Candidates ◽  
Gaucher Disease Type 1 ◽  
Biotechnology Companies ◽  
Approved Drugs ◽  
Novel Drug ◽  
Early Drug

Historically, most Federal Drug Administration-approved drugs were the result of “in-house” efforts within large pharmaceutical companies. Over the last two decades, this paradigm has steadily shifted as the drug industry turned to startups, small biotechnology companies, and academia for the identification of novel drug targets and early drug candidates. This strategic pivot has created new opportunities for groups less traditionally associated with the creation of novel therapeutics, including small academic laboratories, for engagement in the drug discovery process. A recent example of the successful development of a drug that had its origins in academia is eliglustat tartrate, an oral agent for Gaucher disease type 1.

scholarly journals SELDI ProteinChip®Array Technology: Protein-Based Predictive Medicine and Drug Discovery Applications

2003 ◽  
Vol 2003 (4) ◽  
pp. 237-241 ◽  
Author(s):  
Guru Reddy ◽  
Enrique A. Dalmasso
Keyword(s):  
Drug Discovery ◽  
Drug Targets ◽  
Treatment Options ◽  
Drug Effects ◽  
Proteome Analysis ◽  
Predictive Medicine ◽  
Protein Drug ◽  
Proteinchip Array ◽  
Drug Candidates ◽  
Array Technology

Predictive medicine, utilizing the ProteinChip®Array technology, will develop through the implementation of novel biomarkers and multimarker patterns for detecting disease, determining patient prognosis, monitoring drug effects such as efficacy or toxicity, and for defining treatment options. These biomarkers may also serve as novel protein drug candidates or protein drug targets. In addition, the technology can be used for discovering small molecule drugs or for defining their mode of action utilizing protein-based assays. In this review, we describe the following applications of the ProteinChip Array technology: (1) discovery and identification of novel inhibitors of HIV-1 replication, (2) serum and tissue proteome analysis for the discovery and development of novel multimarker clinical assays for prostate, breast, ovarian, and other cancers, and (3) biomarker and drug discovery applications for neurological disorders.

scholarly journals Glutamate Racemase Mutants of Bacillus anthracis

2015 ◽  
Vol 197 (11) ◽  
pp. 1854-1861 ◽  
Author(s):  
So-Young Oh ◽  
Stefan G. Richter ◽  
Dominique M. Missiakas ◽  
Olaf Schneewind
Keyword(s):  
Glutamic Acid ◽  
Bacillus Anthracis ◽  
Causative Agent ◽  
Bacterial Growth ◽  
Bacterial Infections ◽  
Content Type ◽  
Antibiotic Development ◽  
Drug Candidates ◽  
Glutamate Racemase ◽  
Cell Shapes

ABSTRACTd-Glutamate is an essential component of bacterial peptidoglycan and a building block of the poly-γ-d-glutamic acid (PDGA) capsule ofBacillus anthracis, the causative agent of anthrax. Earlier work suggested that two glutamate racemases, encoded byracE1andracE2, are each essential for growth ofB. anthracis, supplyingd-glutamic acid for the synthesis of peptidoglycan and PDGA capsule. Earlier work could not explain, however, why two enzymes that catalyze the same reaction may be needed for bacterial growth. Here, we report that deletion ofracE1orracE2did not prevent growth ofB. anthracisSterne (pXO1+pXO2−), the noncapsulating vaccine strain, or ofB. anthracisAmes (pXO1+pXO2+), a fully virulent, capsulating isolate. While mutants with deletions inracE1andracE2were not viable,racE2deletion delayed vegetative growth ofB. anthracisfollowing spore germination and caused aberrant cell shapes, phenotypes that were partially restored by exogenousd-glutamate. Deletion ofracE1orracE2fromB. anthracisAmes did not affect the production or stereochemical composition of the PDGA capsule. A model is presented wherebyB. anthracis, similar toBacillus subtilis, utilizes two functionally redundant racemase enzymes to synthesized-glutamic acid for peptidoglycan synthesis.IMPORTANCEGlutamate racemases, enzymes that convertl-glutamate tod-glutamate, are targeted for antibiotic development. Glutamate racemase inhibitors may be useful for the treatment of bacterial infections such as anthrax, where the causative agent,B. anthracis, requiresd-glutamate for the synthesis of peptidoglycan and poly-γ-d-glutamic acid (PDGA) capsule. Here we show thatB. anthracispossesses two glutamate racemase genes that can be deleted without abolishing either bacterial growth or PDGA synthesis. These data indicate that drug candidates must inhibit both glutamate racemases, RacE1 and RacE2, in order to blockB. anthracisgrowth and achieve therapeutic efficacy.

scholarly journals Translational and Clinical Pharmacology Considerations in Drug Repurposing for X-linked Adrenoleukodystrophy-A Rare Peroxisomal Disorder

2021 ◽  
Author(s):  
Julianne Tieu ◽  
Siddhee Sahasrabudhe ◽  
Paul Orchard ◽  
James Cloyd ◽  
Reena Kartha
Keyword(s):  
Drug Target ◽  
Drug Targets ◽  
Drug Repurposing ◽  
Pharmacokinetics And Pharmacodynamics ◽  
Drug Candidates ◽  
Target Patient Population ◽  
Site Of Action ◽  
Repurposed Drugs ◽  
Gait Disturbances ◽  
Spastic Quadriparesis

X-linked adrenoleukodystrophy (X-ALD) is an inherited, neurodegenerative rare disease that can result in devastating symptoms of blindness, gait disturbances, and spastic quadriparesis due to progressive demyelination. Typically, the disease progresses rapidly, causing death within the first decade of life. With limited treatments available, efforts to determine an effective therapy that can alter disease progression or mitigate symptoms have been undertaken for many years, particularly through drug repurposing. Repurposing has generally been guided through clinical experience and small trials. At this time, none of the drug candidates have been approved for use, which may be due, in part, to the lack of pharmacokinetic/pharmacodynamic (PK/PD) information on the repurposed medications in the target patient population. Greater consideration for the disease pathophysiology, drug pharmacology, and potential drug-target interactions, specifically at the site of action, would improve drug repurposing and facilitate development. Although there is a good understanding of X-ALD pathophysiology, the absence of information on drug targets, pharmacokinetics, and pharmacodynamics hinders the repurposing of drugs for this condition. Incorporating advanced translational and clinical pharmacological approaches in preclinical studies and early stages clinical trials will improve the success of repurposed drugs for X-ALD as well as other rare diseases.

An insight into anti-arthritic property of phytochemicals against Rheumatoid arthritis using molecular modelling and docking approach

2021 ◽  
Vol 16 (12) ◽  
pp. 185-195
Author(s):  
Bharathi Nathan ◽  
Sudheer M.M. Mohammed
Keyword(s):  
Rheumatoid Arthritis ◽  
Drug Targets ◽  
Joint Inflammation ◽  
Binding Energies ◽  
Multiple Drug ◽  
Matrix Metalloproteinase 3 ◽  
Drug Candidates ◽  
Docking Tool ◽  
Docking Approach ◽  
Interleukin 23

Arthritis literally refers “joint inflammation”, it is a condition where one or more joints are inflamed. More than 100 different types of Arthritis were identified, most common types are rheumatoid arthritis and osteoarthritis. The present study mainly focuses on the development of the novel phytochemical inhibitors against rheumatoid arthritis and osteoarthritis using an integrative cheminformatics drug discovery platform. In this study, we identified potential 405 phytochemical drug candidates, screened against eight selected targets of rheumatoid arthritis and osteoarthritis using molecular docking tool AutoDock. Three phytochemicals Withanolide, Diosgenin and bamyrin exhibited promising binding towards multiple drug targets selected for this study. When comparing with the binding between reference drugs, withanolide showed highest activity against Interleukin-23, Matrix metalloproteinase-3 and Interleukin 8 with binding energies -11.6, -9.4 and -8.3 kcal/mol respectively. Diosgenin also exhibited best activity against three targets that were Interleukin-23, JNK alpha and MMP-3 with -11.3, -10.4, -9.5 kcal/mol binding energies respectively. This study may be important contributing factor to develop new therapeutic drugs for rheumatoid arthritis and osteoarthritis.

Drugs for Targeted Therapies of Alzheimer’s Disease

2019 ◽  
Vol 26 (2) ◽  
pp. 335-359 ◽  
Author(s):  
Chit Tam ◽  
Jack Ho Wong ◽  
Tzi Bun Ng ◽  
Stephen Kwok Wing Tsui ◽  
Tao Zuo
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Clinical Trial ◽  
Drug Targets ◽  
The Elderly ◽  
Dependent Manner ◽  
Cell Replacement Therapy ◽  
Drug Candidates ◽  
Amyloid A ◽  
Potential Drug Targets

Alzheimer’s disease (AD) is one type of neurodegenerative diseases, which is prevalent in the elderly. Beta-amyloid (Aβ) plaques and phosphorylated tau-induced neurofibrillary tangles are two pathological hallmarks of this disease and the corresponding pathological pathways of these hallmarks are considered as the therapeutic targets. There are many drugs scheduled for pre-clinical and clinical trial that target to inhibit the initiators of pathological Aβ and tau aggregates as well as critical Aβ secretases and kinases in tau hyperphosphorylation. In addition, studies in disease gene variations, and detection of key prognostic effectors in early development are also important for AD control. The discovery of potential drug targets contributed to targeted therapy in a stage-dependent manner, However, there are still some issues that cause concern such as the low bioavailability and low efficacy of candidate drugs from clinical trial reports. Therefore, modification of drug candidates and development of delivery agents are essential and critical. With other medical advancements like cell replacement therapy, there is hope for the cure of Alzheimer’s disease in the foreseeable future.

scholarly journals Machine Learning Methods in Drug Discovery

Molecules ◽  
2020 ◽  
Vol 25 (22) ◽  
pp. 5277
Author(s):  
Lauv Patel ◽  
Tripti Shukla ◽  
Xiuzhen Huang ◽  
David W. Ussery ◽  
Shanzhi Wang
Keyword(s):  
Machine Learning ◽  
Deep Learning ◽  
Drug Discovery ◽  
High Throughput Screening ◽  
Drug Targets ◽  
Learning Algorithms ◽  
Machine Learning Techniques ◽  
Online Information ◽  
Drug Candidates ◽  
Novel Drug

The advancements of information technology and related processing techniques have created a fertile base for progress in many scientific fields and industries. In the fields of drug discovery and development, machine learning techniques have been used for the development of novel drug candidates. The methods for designing drug targets and novel drug discovery now routinely combine machine learning and deep learning algorithms to enhance the efficiency, efficacy, and quality of developed outputs. The generation and incorporation of big data, through technologies such as high-throughput screening and high through-put computational analysis of databases used for both lead and target discovery, has increased the reliability of the machine learning and deep learning incorporated techniques. The use of these virtual screening and encompassing online information has also been highlighted in developing lead synthesis pathways. In this review, machine learning and deep learning algorithms utilized in drug discovery and associated techniques will be discussed. The applications that produce promising results and methods will be reviewed.

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