Bioinfomatics as a Tool in Drug Designing

Worldwide, colorectal cancer takes up the third position in commonly detected cancer and fourth in cancer mortality. Recent progress in molecular modeling studies has led to significant success in drug discovery using structure and ligand-based methods. This study highlights aspects of the anticancer drug design. The structure and ligand-based drug design are discussed to investigate the molecular and quantum mechanics in anti-cancer drugs. Recent advances in anticancer agent identification driven by structural and molecular insights are presented. As a result, the recent advances in the field and the current scenario in drug designing of cancer drugs are discussed. This review provides information on how cancer drugs were formulated and identified using computational power by the drug discovery society.

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Next-Generation Sequencing: An Emerging Tool for Drug Designing

Current Pharmaceutical Design ◽

10.2174/1381612825666190911155508 ◽

2019 ◽

Vol 25 (31) ◽

pp. 3350-3357 ◽

Cited By ~ 1

Author(s):

Pooja Tripathi ◽

Jyotsna Singh ◽

Jonathan A. Lal ◽

Vijay Tripathi

Keyword(s):

Next Generation Sequencing ◽

High Throughput ◽

Large Scale ◽

Massively Parallel Sequencing ◽

Genomic Research ◽

Biological Research ◽

Next Generation ◽

Human Welfare ◽

Drug Designing ◽

Generation Sequencing

Background: With the outbreak of high throughput next-generation sequencing (NGS), the biological research of drug discovery has been directed towards the oncology and infectious disease therapeutic areas, with extensive use in biopharmaceutical development and vaccine production. Method: In this review, an effort was made to address the basic background of NGS technologies, potential applications of NGS in drug designing. Our purpose is also to provide a brief introduction of various Nextgeneration sequencing techniques. Discussions: The high-throughput methods execute Large-scale Unbiased Sequencing (LUS) which comprises of Massively Parallel Sequencing (MPS) or NGS technologies. The Next geneinvolved necessarily executes Largescale Unbiased Sequencing (LUS) which comprises of MPS or NGS technologies. These are related terms that describe a DNA sequencing technology which has revolutionized genomic research. Using NGS, an entire human genome can be sequenced within a single day. Conclusion: Analysis of NGS data unravels important clues in the quest for the treatment of various lifethreatening diseases and other related scientific problems related to human welfare.

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Use of Molecular Dynamics Simulations in Structure-Based Drug Discovery

Current Pharmaceutical Design ◽

10.2174/1381612825666190903153043 ◽

2019 ◽

Vol 25 (31) ◽

pp. 3339-3349 ◽

Cited By ~ 6

Author(s):

Indrani Bera ◽

Pavan V. Payghan

Keyword(s):

Molecular Dynamics ◽

Drug Discovery ◽

Molecular Dynamics Simulations ◽

Drug Target ◽

Structural Information ◽

Drug Binding ◽

Structure Based Drug Design ◽

Drug Designing ◽

Target Binding ◽

Dynamics Simulations

Background: Traditional drug discovery is a lengthy process which involves a huge amount of resources. Modern-day drug discovers various multidisciplinary approaches amongst which, computational ligand and structure-based drug designing methods contribute significantly. Structure-based drug designing techniques require the knowledge of structural information of drug target and drug-target complexes. Proper understanding of drug-target binding requires the flexibility of both ligand and receptor to be incorporated. Molecular docking refers to the static picture of the drug-target complex(es). Molecular dynamics, on the other hand, introduces flexibility to understand the drug binding process. Objective: The aim of the present study is to provide a systematic review on the usage of molecular dynamics simulations to aid the process of structure-based drug design. Method: This review discussed findings from various research articles and review papers on the use of molecular dynamics in drug discovery. All efforts highlight the practical grounds for which molecular dynamics simulations are used in drug designing program. In summary, various aspects of the use of molecular dynamics simulations that underline the basis of studying drug-target complexes were thoroughly explained. Results: This review is the result of reviewing more than a hundred papers. It summarizes various problems that use molecular dynamics simulations. Conclusion: The findings of this review highlight how molecular dynamics simulations have been successfully implemented to study the structure-function details of specific drug-target complexes. It also identifies the key areas such as stability of drug-target complexes, ligand binding kinetics and identification of allosteric sites which have been elucidated using molecular dynamics simulations.

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Microbial Bioconversion: A Regio-specific Method for Novel Drug Design and Toxicological Study of Metabolites

Current Pharmaceutical Biotechnology ◽

10.2174/1389201020666190618115821 ◽

2019 ◽

Vol 20 (14) ◽

pp. 1156-1162

Author(s):

Maria Yousuf ◽

Waqas Jamil ◽

Khayala Mammadova

Keyword(s):

Microbial Transformation ◽

Specific Method ◽

Reaction Conditions ◽

Small Organic Molecules ◽

Toxicological Studies ◽

Drug Designing ◽

Transformation Methods ◽

Novel Drug

The methods of chemical structural alteration of small organic molecules by using microbes (fungi, bacteria, yeast, etc.) are gaining tremendous attention to obtain structurally novel and therapeutically potential leads. The regiospecific mild environmental friendly reaction conditions with the ability of novel chemical structural modification in compounds categorize this technique; a distinguished and unique way to obtain medicinally important drugs and their in vivo mimic metabolites with costeffective and timely manner. This review article shortly addresses the immense pharmaceutical importance of microbial transformation methods in drug designing and development as well as the role of CYP450 enzymes in fungi to obtain in vivo drug metabolites for toxicological studies.

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Experimental and Computational Approaches to Improve Binding Affinity in Chemical Biology and Drug Discovery

Current Topics in Medicinal Chemistry ◽

10.2174/156802662019200701164759 ◽

2020 ◽

Vol 20 (19) ◽

pp. 1651-1660

Author(s):

Anuraj Nayarisseri

Keyword(s):

Drug Discovery ◽

Drug Design ◽

Binding Affinity ◽

Chemical Biology ◽

De Novo ◽

Structure Based Drug Design ◽

Computational Approaches ◽

Drug Designing ◽

Traditional Drug ◽

Computer Based

Drug discovery is one of the most complicated processes and establishment of a single drug may require multidisciplinary attempts to design efficient and commercially viable drugs. The main purpose of drug design is to identify a chemical compound or inhibitor that can bind to an active site of a specific cavity on a target protein. The traditional drug design methods involved various experimental based approaches including random screening of chemicals found in nature or can be synthesized directly in chemical laboratories. Except for the long cycle design and time, high cost is also the major issue of concern. Modernized computer-based algorithm including structure-based drug design has accelerated the drug design and discovery process adequately. Surprisingly from the past decade remarkable progress has been made concerned with all area of drug design and discovery. CADD (Computer Aided Drug Designing) based tools shorten the conventional cycle size and also generate chemically more stable and worthy compounds and hence reduce the drug discovery cost. This special edition of editorial comprises the combination of seven research and review articles set emphasis especially on the computational approaches along with the experimental approaches using a chemical synthesizing for the binding affinity in chemical biology and discovery as a salient used in de-novo drug designing. This set of articles exfoliates the role that systems biology and the evaluation of ligand affinity in drug design and discovery for the future.

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DFT based computational methodology of IC50 prediction

Current Computer - Aided Drug Design ◽

10.2174/1573409916666200219115112 ◽

2020 ◽

Vol 16 ◽

Author(s):

Arijit Bag

Keyword(s):

Present Method ◽

Dipole Moments ◽

Research Work ◽

Organometallic Compounds ◽

Computational Method ◽

Unknown Compound ◽

Drug Designing ◽

Further Development ◽

Similar Kind ◽

Hiv 1

Background: IC50 is one of the most important parameters of a drug. But, it is very difficult to predict this value of a new compound without experiment. There are only a few QSAR based methods available for IC50 prediction which is also highly dependable on huge number of known data. Thus, there is an immense demand for a sophisticated computational method of IC50 prediction, in the field of in-silico drug designing. Objective: Recently developed quantum computation based method of IC50 prediction by Bag and Ghorai requires an affordable known data. In present research work further development of this method is carried out such that the requisite number of known data being minimal. Methods: To retrench the cardinal data span and shrink the effects of variant biological parameters on the computed value of IC50, a relative approach of IC50 computation is pursued in the present method. To predict an approximate value of IC50 of a small molecule, only the IC50 of a similar kind of molecule is required for this method. Results: The present method of IC50 computation is tested for both organic and organometallic compounds as HIV-1 capsid A inhibitor and cancer drugs. Computed results match very well with the experiment. Conclusion: This method is easily applicable to both organic and organometallic com- pounds with acceptable accuracy. Since this method requires only the dipole moments of an unknown compound and the reference compound, IC50 based drug search is possible with this method. An algorithm is proposed here for IC50 based drug search.

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Molecular Docking Study for Analyzing the Inhibitory Effect of Anti-inflammatory Plant Compound Against Tumour Necrosis Factor (TNF-α)

Current Drug Therapy ◽

10.2174/1574885513666180503145352 ◽

2019 ◽

Vol 14 (1) ◽

pp. 85-90

Author(s):

Sagarika Biswas

Keyword(s):

Molecular Docking ◽

Tumour Necrosis Factor ◽

Tumour Necrosis ◽

Docking Study ◽

Developed Countries ◽

Inhibitory Effect ◽

Molecular Docking Study ◽

Drug Designing ◽

Anti Inflammatory ◽

Necrosis Factor

Background: Rheumatoid Arthritis (RA) is an autoimmune disorder of symmetric synovial joints which is characterized by the chronic inflammation with 0.5-1% prevalence in developed countries. Presence of persistent inflammation is attributed to the major contribution of key inflammatory cytokine and tumour necrosis factor- alpha (TNF- α). Recent drug designing studies are developing TNF-α blockers to provide relief from the symptoms of the disease such as pain and inflammation. Available blockers are showing certain limitations such as it may enhance the rate of tuberculosis (TB) occurrence, lymphoma risk, cost issues and certain infections are major concern. Discussed limitations implicated a need of development of some alternative drugs which exhibit fewer side effects with low cost. Therefore, we have identified anti-inflammatory compounds in an underutilized fruit of Baccaurea sapida (B.sapida) in our previous studies. Among them quercetin have been identified as the most potent lead compound for drug designing studies of RA. Methods: In the present article, characterization of quercetin has been carried out to check its drug likeliness and molecular docking study has been carried out between TNF- α and quercetin by using AutoDock 4.2.1 software. Further, inhibitory effect of B. sapida fruit extract on RA plasma has been analysed through immunological assay ELISA. Results: Our in-silico analysis indicated that quercetin showed non carcinogenic reaction in animal model and it may also cross the membrane barrier easily. We have studied the ten different binding poses and best binding pose of TNF-α and quercetin showed -6.3 kcal/mol minimum binding energy and 23.94 µM inhibitory constant. In addition to this, ELISA indicated 2.2 down regulated expression of TNF-α in RA compared to control. Conclusion: This study may further be utilized for the drug designing studies to reduce TNF-α mediated inflammation in near future. This attempt may also enhance the utilization of this plant worldwide.

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