Modern Paradigm Towards Potential Target Identification for Antiviral (SARS-nCoV-2) and Anticancer Lipopeptides: A Pharmacophore-Based Approach

2022 ◽  
Author(s):  
Manisha Yadav ◽  
J. Satya Eswari
Keyword(s):  
Drug Discovery ◽  
Target Identification ◽  
Target Prediction ◽  
Cost Effective ◽  
Time Saving ◽  
Web Based ◽  
Target Proteins ◽  
Lead Compounds ◽  
Potential Target ◽  
Biopharmaceutical Properties

Background: Lipopeptides are potential microbial metabolites that are abandoned with broad spectrum biopharmaceutical properties ranging from antimicrobial, antiviral and anticancer, etc. Clinical studies are not much explored beyond the experimental methods to understand drug mechanisms on target proteins at the molecular level for large molecules. Due to the less available studies on potential target proteins of lipopeptide based drugs, their potential inhibitory role for more obvious treatment on disease have not been explored in the direction of lead optimization. However, Computational approaches need to be utilized to explore drug discovery aspects on lipopeptide based drugs, which are time saving and cost-effective techniques. Methods: Here a ligand-based drug discovery approach is coupled with reverse pharmacophore-mapping for the prediction of potential targets for antiviral (SARS-nCoV-2) and anticancer lipopeptides. Web-based servers PharmMapper and Swiss Target Prediction are used for the identification of target proteins for lipopeptides surfactin and iturin produced by Bacillus subtilis. Results: The studies have given the insight to treat the diseases with next-generation large molecule therapeutics. Results also indicate the affinity for Angiotensin-Converting Enzymes (ACE) and proteases as the potential viral targets for these categories of peptide therapeutics. A target protein for the Human Papilloma Virus (HPV) has also been mapped. Conclusion: The work will further help in exploring computer-aided drug designing of novel compounds with greater efficiency where the structure of the target proteins and lead compounds are known.  

scholarly journals Structure-guided, target-based drug discovery – exploiting genome information from HIV to mycobacterial infections

2016 ◽  
Vol 62 (3) ◽  
pp. 262-272
Author(s):  
Sony Malhotra ◽  
Sherine E. Thomas ◽  
Bernardo Ochoa Montano ◽  
Tom L. Blundell
Keyword(s):  
Drug Discovery ◽  
Binding Sites ◽  
Target Identification ◽  
Hiv Protease ◽  
Inhibitor Binding ◽  
Mycobacterial Infections ◽  
Lead Compounds ◽  
Lead Optimisation ◽  
Genome Information ◽  
Fragment Based Drug Discovery

The use of protein crystallography in structure-guided drug discovery allows identification of potential inhibitor-binding sites and optimisation of interactions of hits and lead compounds with a target protein. An early example of this approach was the use of the structure of HIV protease in designing AIDS antivirals. More recently, use of structure-guided design with fragment-based drug discovery, which reduces the size of screening libraries by decreasing complexity, has improved ligand efficiency in drug design. Here, we discuss the use of structure-guided target identification and lead optimisation using fragment-based approaches in the development of new antimicrobials for mycobacterial infections.

scholarly journals Target Identification Using Homopharma and Network-Based Methods for Predicting Compounds Against Dengue Virus-Infected Cells

Molecules ◽  
2020 ◽  
Vol 25 (8) ◽  
pp. 1883 ◽  
Author(s):  
Kowit Hengphasatporn ◽  
Kitiporn Plaimas ◽  
Apichat Suratanee ◽  
Peemapat Wongsriphisant ◽  
Jinn-Moon Yang ◽  
...  
Keyword(s):  
Drug Discovery ◽  
Target Identification ◽  
Antiviral Agents ◽  
Antiviral Drug ◽  
Target Prediction ◽  
Denv Infection ◽  
Inhibitory Effect ◽  
Active Compounds ◽  
Phenolic Lipids ◽  
Human Proteins

Drug target prediction is an important method for drug discovery and design, can disclose the potential inhibitory effect of active compounds, and is particularly relevant to many diseases that have the potential to kill, such as dengue, but lack any healing agent. An antiviral drug is urgently required for dengue treatment. Some potential antiviral agents are still in the process of drug discovery, but the development of more effective active molecules is in critical demand. Herein, we aimed to provide an efficient technique for target prediction using homopharma and network-based methods, which is reliable and expeditious to hunt for the possible human targets of three phenolic lipids (anarcardic acid, cardol, and cardanol) related to dengue viral (DENV) infection as a case study. Using several databases, the similarity search and network-based analyses were applied on the three phenolic lipids resulting in the identification of seven possible targets as follows. Based on protein annotation, three phenolic lipids may interrupt or disturb the human proteins, namely KAT5, GAPDH, ACTB, and HSP90AA1, whose biological functions have been previously reported to be involved with viruses in the family Flaviviridae. In addition, these phenolic lipids might inhibit the mechanism of the viral proteins: NS3, NS5, and E proteins. The DENV and human proteins obtained from this study could be potential targets for further molecular optimization on compounds with a phenolic lipid core structure in anti-dengue drug discovery. As such, this pipeline could be a valuable tool to identify possible targets of active compounds.

scholarly journals Design of Druglike Small Molecules for Possible Inhibition of Antiapoptotic BCL-2, BCL-W, and BFL-1 Proteins

2010 ◽  
Vol 2 ◽  
pp. BECB.S5575 ◽  
Author(s):  
D.S. Dalafave
Keyword(s):  
Drug Discovery ◽  
Small Molecules ◽  
Cost Effective ◽  
Effective Procedure ◽  
Lead Compounds ◽  
Single Protein ◽  
Computational Resources ◽  
The Cost ◽  
Early Phases

New druglike small molecules with possible anticancer applications were computationally designed. The molecules formed stable complexes with antiapoptotic BCL-2, BCL-W, and BFL-1 proteins. These findings are novel because, to the best of the author's knowledge, molecules that bind all three of these proteins are not known. A drug based on them should be more economical and better tolerated by patients than a combination of drugs, each targeting a single protein. The calculated drug-related properties of the molecules were similar to those found in most commercial drugs. The molecules were designed and evaluated following a simple, yet effective procedure. The need for substantial computational resources often precludes researchers in many countries and small institutions from participating in the field. The procedure presented here offsets the problem by reducing the cost of involvement. The procedure can be used efficiently in the early phases of drug discovery to evaluate promising lead compounds in time- and cost-effective ways.

PENERAPAN METODE PROTOTYPING PADA PERANCANGAN APLIKASI SPPD KPPN MEDAN II BERBASIS WEBSITE

2019 ◽  
Vol 11 (1) ◽  
pp. 8-19
Author(s):  
Crystal Jelita Lumban Tobing
Keyword(s):  
Time Saving ◽  
Web Based ◽  
Government Organization ◽  
Manual Method ◽  
Microsoft Word ◽  
Ministry Of Finance ◽  
The Government ◽  
The City ◽  
Employee Data ◽  
The Web

 KPPN Medan II is one of the government organization units at the Ministry of Finance. Where leaders and employees who work at KPPN Medan II always carry out official trips between cities and outside the city. With these conditions, making SPPD documents experiencing the intensity of official travel activities carried out by employees of KPPN Medan II can be said frequently. So that in making SPPD in KPPN Medan II is still using the manual method that is recording through Microsoft Word which in the sense is less effective and efficient. In naming employees who get official assignments, officers manually entering employee data that receives official travel letters are prone to being lost because data is manually written. The web-based SPPD application is built by applying this prototyping method which is expected to facilitate SPPD KPPN Medan II management officers in making SPPD that is effective, efficient, accurate, time-saving, and not prone to losing SPPD data of KPPN Medan II employees who will has made official trips due to the existence of a special database to accommodate all SPPD files.

E-Voting Kepala Desa dan Modal Sosial

2019 ◽  
Vol 2 (6) ◽  
pp. 759
Author(s):  
Khaulah Afifah ◽  
Lala M Kolopaking ◽  
Zessy Ardinal Barlan
Keyword(s):  
Social Capital ◽  
Random Sampling ◽  
Qualitative Data ◽  
Sampling Technique ◽  
Cost Effective ◽  
Simple Random Sampling ◽  
Community Based ◽  
Time Saving ◽  
The Social ◽  
Voting System

Head of a village election with e-voting system is a new thing for community The success level of e-voting system can be reached by fulfil several principles in order to the implementation going effective and the result of the election can be accepted by all. The objectives of this research is to analyze the relation between the success level of e-voting system with social capital of the community. This research is carried out with the quantitative approach and supported by qualitative data. This research takes 60 respondents using simple random sampling technique. The results showed that the success level of e-voting has a correlation with the level of social capital of the community. Based on the field study, the social capital of the community is classified as high. The high social capital makes the implementation of e-voting successful and the success level is also high, because in the election ten years ago occurred a conflict. The community considers e-voting easier and more practical, cost effective and time-saving, and the results of e-voting are also reliable. A practical and fast of e-voting system can be a solution especially for “rural-urban” community who are busy or work outside the village.Keywords: E-voting, the success level of the system, social capital Pemilihan kepala desa dengan sistem e-voting merupakan hal yang baru bagi masyarakat. Keberhasilan penerapan sistem e-voting dilihat dari terpenuhinya beberapa prinsip agar penerapannya berlangsung efektif dan hasilnya dapat diterima oleh seluruh masyarakat. Penelitian ini bertujuan untuk menganalisis hubungan tingkat keberhasilan sistem e-voting dalam pemilihan kepala desa dengan tingkat modal sosial masyarakat. Bentuk penelitian ini adalah penelitian kuantitatif yang didukung oleh analisis data kualitatif. Penelitian ini mengambil enam puluh responden dengan teknik simple random sampling. Hasil penelitian menunjukkan bahwa tingkat keberhasilan e-voting memiliki hubungan dengan tingkat modal sosial masyarakat. Berdasarkan kajian di lapang, modal sosial masyarakat tergolong tinggi. Tingginya modal sosial tersebut membuat pelaksanaan e-voting berhasil dan tingkat keberhasilannya juga tergolong tinggi karena pada pemilihan sepuluh tahun silam sempat terjadi konflik. Masyarakat menganggap sistem evoting lebih mudah dan praktis, hemat dalam segi biaya dan waktu, serta hasil dari pemilihan juga dapat dipertanggungjawabkan. Sistem e-voting yang praktis dan cepat dapat menjadi solusi khususnya bagi masyarakat daerah “desa-kota” yang memiliki kesibukan atau pekerjaan di luar desa.Kata Kunci: E-voting, keberhasilan sistem, modal sosial. 

Mapping of Protein-Protein Interactions: Web-Based Resources for Revealing Interactomes

2019 ◽  
Vol 26 (21) ◽  
pp. 3890-3910 ◽  
Author(s):  
Branislava Gemovic ◽  
Neven Sumonja ◽  
Radoslav Davidovic ◽  
Vladimir Perovic ◽  
Nevena Veljkovic
Keyword(s):  
Drug Discovery ◽  
Protein Interactions ◽  
Protein Complexes ◽  
Experimental Studies ◽  
Protein Protein Interactions ◽  
Web Based ◽  
Prediction Tools ◽  
Physiological Processes ◽  
Modern Drug ◽  
Ppi Prediction

Background: The significant number of protein-protein interactions (PPIs) discovered by harnessing concomitant advances in the fields of sequencing, crystallography, spectrometry and two-hybrid screening suggests astonishing prospects for remodelling drug discovery. The PPI space which includes up to 650 000 entities is a remarkable reservoir of potential therapeutic targets for every human disease. In order to allow modern drug discovery programs to leverage this, we should be able to discern complete PPI maps associated with a specific disorder and corresponding normal physiology. Objective: Here, we will review community available computational programs for predicting PPIs and web-based resources for storing experimentally annotated interactions. Methods: We compared the capacities of prediction tools: iLoops, Struck2Net, HOMCOS, COTH, PrePPI, InterPreTS and PRISM to predict recently discovered protein interactions. Results: We described sequence-based and structure-based PPI prediction tools and addressed their peculiarities. Additionally, since the usefulness of prediction algorithms critically depends on the quality and quantity of the experimental data they are built on; we extensively discussed community resources for protein interactions. We focused on the active and recently updated primary and secondary PPI databases, repositories specialized to the subject or species, as well as databases that include both experimental and predicted PPIs. Conclusion: PPI complexes are the basis of important physiological processes and therefore, possible targets for cell-penetrating ligands. Reliable computational PPI predictions can speed up new target discoveries through prioritization of therapeutically relevant protein–protein complexes for experimental studies.

Recent Advances in Drug Repurposing for Parkinson’s Disease

2019 ◽  
Vol 26 (28) ◽  
pp. 5340-5362 ◽  
Author(s):  
Xin Chen ◽  
Giuseppe Gumina ◽  
Kristopher G. Virga
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Drug Discovery ◽  
De Novo ◽  
Drug Repositioning ◽  
Drug Repurposing ◽  
Cost Effective ◽  
New Drugs ◽  
Recent Advances ◽  
Clinical Drugs

:As a long-term degenerative disorder of the central nervous system that mostly affects older people, Parkinson’s disease is a growing health threat to our ever-aging population. Despite remarkable advances in our understanding of this disease, all therapeutics currently available only act to improve symptoms but cannot stop the disease progression. Therefore, it is essential that more effective drug discovery methods and approaches are developed, validated, and used for the discovery of disease-modifying treatments for Parkinson’s disease. Drug repurposing, also known as drug repositioning, or the process of finding new uses for existing or abandoned pharmaceuticals, has been recognized as a cost-effective and timeefficient way to develop new drugs, being equally promising as de novo drug discovery in the field of neurodegeneration and, more specifically for Parkinson’s disease. The availability of several established libraries of clinical drugs and fast evolvement in disease biology, genomics and bioinformatics has stimulated the momentums of both in silico and activity-based drug repurposing. With the successful clinical introduction of several repurposed drugs for Parkinson’s disease, drug repurposing has now become a robust alternative approach to the discovery and development of novel drugs for this disease. In this review, recent advances in drug repurposing for Parkinson’s disease will be discussed.

Current Approaches to Drug Discovery for Chagas Disease: Methodological Advances

2019 ◽  
Vol 22 (8) ◽  
pp. 509-520
Author(s):  
Cauê B. Scarim ◽  
Chung M. Chin
Keyword(s):  
Drug Discovery ◽  
Chagas Disease ◽  
Drug Candidates ◽  
Lead Compounds ◽  
New Drug ◽  
Compound Libraries ◽  
Screening Assays ◽  
Cruzi Infection

Background: In recent years, there has been an improvement in the in vitro and in vivo methodology for the screening of anti-chagasic compounds. Millions of compounds can now have their activity evaluated (in large compound libraries) by means of high throughput in vitro screening assays. Objective: Current approaches to drug discovery for Chagas disease. Method: This review article examines the contribution of these methodological advances in medicinal chemistry in the last four years, focusing on Trypanosoma cruzi infection, obtained from the PubMed, Web of Science, and Scopus databases. Results: Here, we have shown that the promise is increasing each year for more lead compounds for the development of a new drug against Chagas disease. Conclusion: There is increased optimism among those working with the objective to find new drug candidates for optimal treatments against Chagas disease.

Drug repurposing using similarity-based target prediction, docking studies and scaffold hopping of lefamulin

2020 ◽  
Vol 17 ◽  
Author(s):  
Shikha Sharma ◽  
Shweta Sharma ◽  
Vaishali Pathak ◽  
Parwinder Kaur ◽  
Rajesh Kumar Singh
Keyword(s):  
In Silico ◽  
Target Prediction ◽  
Drug Repurposing ◽  
Docking Studies ◽  
Target Protein ◽  
Future Perspective ◽  
Antibacterial Drug ◽  
Scaffold Hopping ◽  
Target Proteins ◽  
Renin Inhibitors

Aim: To investigate and validate the potential target proteins for drug repurposing of newly FDA approved antibacterial drug. Background: Drug repurposing is the process of assigning indications for drugs other than the one(s) that they were initially developed for. Discovery of entirely new indications from already approved drugs is highly lucrative as it minimizes the pipeline of the drug development process by reducing time and cost. In silico driven technologies made it possible to analyze molecules for different target proteins which are not yet explored. Objective: To analyze possible targets proteins for drug repurposing of lefamulin and their validation. Also, in silico prediction of novel scaffolds from lefamulin has been performed for assisting medicinal chemists in future drug design. Methods: A similarity-based prediction tool was employed for predicting target protein and further investigated using docking studies on PDB ID: 2V16. Besides, various in silico tools were employed for prediction of novel scaffolds from lefamulin using scaffold hopping technique followed by evaluation with various in silico parameters viz., ADME, synthetic accessibility and PAINS. Results: Based on the similarity and target prediction studies, renin is found as the most probable target protein for lefamulin. Further, validation studies using docking of lefamulin revealed the significant interactions of lefamulin with the binding pocket of the target protein. Also, three novel scaffolds were predicted using scaffold hopping technique and found to be in the limit to reduce the chances of drug failure in the physiological system during the last stage approval process. Conclusion: To encapsulate the future perspective, lefamulin may assist in the development of the renin inhibitors and, also three possible novel scaffolds with good pharmacokinetic profile can be developed into both as renin inhibitors and for bacterial infections.

Kinetic Behaviour of Amylase According to pH: A New Perspective for Starch Hydrolysis Process

2020 ◽  
Vol 16 (2) ◽  
pp. 135-144
Author(s):  
Ravneet K. Grewal ◽  
Baldeep Kaur ◽  
Gagandeep Kaur
Keyword(s):  
Metal Ions ◽  
Competitive Inhibition ◽  
Deae Cellulose ◽  
Kinetic Studies ◽  
Cost Effective ◽  
Starch Hydrolysis ◽  
Divalent Metal Ions ◽  
Activity Data ◽  
Time Saving ◽  
Alkaline Conditions

Background: Amylases are the most widely used biocatalysts in starch saccharification and detergent industries. However, commercially available amylases have few limitations viz. limited activity at low or high pH and Ca2+ dependency. Objective: The quest for exploiting amylase for diverse applications to improve the industrial processes in terms of efficiency and feasibility led us to investigate the kinetics of amylase in the presence of metal ions as a function of pH. Methods: The crude extract from soil fungal isolate cultures is subjected to salt precipitation, dialysis and DEAE cellulose chromatography followed by amylase extraction and is incubated with divalent metal ions (i.e., Ca2+, Fe2+, Cu2+, and Hg2+); Michaelis-Menton constant (Km), and maximum reaction velocity (Vmax) are calculated by plotting the activity data obtained in the absence and presence of ions, as a function of substrate concentration in Lineweaver-Burk Plot. Results: Kinetic studies reveal that amylase is inhibited un-competitively at 5mM Cu2+ at pH 4.5 and 7.5, but non-competitively at pH 9.5. Non-competitive inhibition of amylase catalyzed starch hydrolysis is observed with 5mM Hg2+ at pH 9.5, which changes to mixed inhibition at pH 4.5 and 7.5. At pH 4.5, Ca2+ induces K- and V-type activation of amylase catalyzed starch hydrolysis; however, the enzyme has V-type activation at 7mM Ca2+ under alkaline conditions. Also, K- and V-type of activation of amylase is observed in the presence of 7mM Fe2+ at pH 4.5 and 9.5. Conclusion: These findings suggest that divalent ions modulation of amylase is pH dependent. Furthermore, a time-saving and cost-effective solution is proposed to overcome the challenges of the existing methodology of starch hydrolysis in starch and detergent industries.

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