It is reported that Alzheimer disease is linked with hypertension, diabetes type 2 and high cholesterolemia. The underlying genetic cause relating these diseases are not well studied clinically. But it has been widely
accepted that beta secretase (BACE1) is the main culprit of causing Alzheimer disease. This enzyme comes under peptidase A1 family. In the present work, ligand based and structure based drug designing have been reported. QSAR studies were done using 21 gallic acid derivatives dataset to develop good predictive
model in order to predict biological activity and certain descriptors was reported to further enhance the
analgesic activity of gallic acid derivatives. Molecular docking studies were performed in order to find
structure based drug design. Two natural gallic acid derivative have been repoted as a potent inhibitor to beta secretase enzyme.
ADMET properties prediction using AI will accelerate the process of drug discovery.
This slide mostly focuses on using graph-based deep learning techniques to predict drug properties.
BOC Sciences aims at developing the most accurate in silico methods to overcome bottlenecks in drug discovery and design innovative medicines to treat important disease.
ADMET properties prediction using AI will accelerate the process of drug discovery.
This slide mostly focuses on using graph-based deep learning techniques to predict drug properties.
BOC Sciences aims at developing the most accurate in silico methods to overcome bottlenecks in drug discovery and design innovative medicines to treat important disease.
THE DRUG DESIGN AND DEVELOPMENT BASED ON DRUG DISCOVERY ,HERE ITS NEED RATIONALE ARE EXPLAINED ALSO QSAR, MOLECULAR DOCKING ITS HISTORY NEED, STRUCTURE BASED DRUG DESIGN IN EASY WAY WE HAVE MENTIONED. THIS WILL MAKE READERS EASY TO COLLECT DATA AT A PLACE ALL OVER THIS IS FOR PHARMA STUDENTS, ACADEMICS, PROFESSIONL AND OST USEFUL FOR RESEARCHERS.
THANK YOU
HOPE YOU WILL LIKE AND SHARE
molecular docking its types and de novo drug design and application and softw...GAUTAM KHUNE
This ppt deals with all the aspects related to molecular docking ,its types(rigid ,flexible and manual) and screening based on it and also deals with de novo drug design , various softwares available for docking methodologies and applications for molecular docking in new drug design
Molecular modelling for in silico drug discoveryLee Larcombe
A slide set based on the small molecule section of "Introduction to in silico drug discovery" with more detail on molecular modelling and simulation aspects. Including a bit more on protein structure prediction
Drug discovery take years to decade for discovering a new drug and very costly
Effort to cut down the research timeline and cost by reducing wet-lab experiment use computer modeling
Others have done the work. Some have used the work. I have spoken only on behalf of their behalf.
Introduction to In silico engineering for biologicsLee Larcombe
A subset of slides from "Introduction to in silico drug discovery" focussed just on the engineering considerations for biologics / antibody therapeutics
Drug designing is a process used in biopharmaceutical industry to discover and develop new drug compounds.
Variety of computational methods are used to identify novel compounds ,design compounds for selectivity and safety.
Structure-based drug design, ligand-based drug design , homology based methods are used depending on how much information is available about drug targets and potential drug compounds.
Stable Drug Designing by Minimizing Drug Protein Interaction Energy Using PSO csandit
Each and every biological function in living organism happens as a result of protein-protein interactions. The diseases are no exception to this. Identifying one or more proteins for a
particular disease and then designing a suitable chemical compound (known as drug) to destroy these proteins has been an interesting topic of research in bio-informatics. In previous methods,drugs were designed using only seven chemical components and were represented as a fixedlength
tree. But in reality, a drug contains many chemical groups collectively known as
pharmacophore. Moreover, the chemical length of the drug cannot be determined before
designing the drug.
In the present work, a Particle Swarm Optimization (PSO) based methodology has been
proposed to find out a suitable drug for a particular disease so that the drug-protein interaction
becomes stable. In the proposed algorithm, the drug is represented as a variable length tree and essential functional groups are arranged in different positions of that drug. Finally, the structure of the drug is obtained and its docking energy is minimized simultaneously. Also, the
orientation of chemical groups in the drug is tested so that it can bind to a particular active site of a target protein and the drug fits well inside the active site of target protein. Here, several inter-molecular forces have been considered for accuracy of the docking energy. Results showthat PSO performs better than the earlier methods.
Each and every biological function in living organism occurs due to protein-protein interactions. The
diseases are no exception to this. Identifying one or more proteins for a particular disease and then
designing a suitable chemical compound (which is known as drug or ligand) to destroy those proteins is a
challenging topic of research in computational biology. In earlier methods, drugs were designed using only
a few chemical components and were represented as a fixed-length tree. But in reality, a drug contains
many chemical groups collectively known as pharmacophore. Moreover, the chemical length of the drug
cannot be determined before designing that drug.
In the present work, a Particle Swarm Optimization (PSO) based methodology has been proposed to find
out a suitable drug for a particular disease so that the drug-target protein interaction energy becomes
minimum. In the proposed algorithm, the drug is represented as a variable length tree and essential
functional groups are arranged in different positions of that drug. Finally, the structure of the drug is
obtained and its docking energy is minimized simultaneously. Also, the orientation of chemical groups in
the drug is tested so that it can bind to a particular active site of a target protein and the drug fits well
inside the active site of target protein. Here, several inter-molecular forces have been considered for
accuracy of the docking energy. Results are demonstrated for three different target proteins both
numerically and pictorially. Results show that PSO performs better than the earlier methods.
THE DRUG DESIGN AND DEVELOPMENT BASED ON DRUG DISCOVERY ,HERE ITS NEED RATIONALE ARE EXPLAINED ALSO QSAR, MOLECULAR DOCKING ITS HISTORY NEED, STRUCTURE BASED DRUG DESIGN IN EASY WAY WE HAVE MENTIONED. THIS WILL MAKE READERS EASY TO COLLECT DATA AT A PLACE ALL OVER THIS IS FOR PHARMA STUDENTS, ACADEMICS, PROFESSIONL AND OST USEFUL FOR RESEARCHERS.
THANK YOU
HOPE YOU WILL LIKE AND SHARE
molecular docking its types and de novo drug design and application and softw...GAUTAM KHUNE
This ppt deals with all the aspects related to molecular docking ,its types(rigid ,flexible and manual) and screening based on it and also deals with de novo drug design , various softwares available for docking methodologies and applications for molecular docking in new drug design
Molecular modelling for in silico drug discoveryLee Larcombe
A slide set based on the small molecule section of "Introduction to in silico drug discovery" with more detail on molecular modelling and simulation aspects. Including a bit more on protein structure prediction
Drug discovery take years to decade for discovering a new drug and very costly
Effort to cut down the research timeline and cost by reducing wet-lab experiment use computer modeling
Others have done the work. Some have used the work. I have spoken only on behalf of their behalf.
Introduction to In silico engineering for biologicsLee Larcombe
A subset of slides from "Introduction to in silico drug discovery" focussed just on the engineering considerations for biologics / antibody therapeutics
Drug designing is a process used in biopharmaceutical industry to discover and develop new drug compounds.
Variety of computational methods are used to identify novel compounds ,design compounds for selectivity and safety.
Structure-based drug design, ligand-based drug design , homology based methods are used depending on how much information is available about drug targets and potential drug compounds.
Stable Drug Designing by Minimizing Drug Protein Interaction Energy Using PSO csandit
Each and every biological function in living organism happens as a result of protein-protein interactions. The diseases are no exception to this. Identifying one or more proteins for a
particular disease and then designing a suitable chemical compound (known as drug) to destroy these proteins has been an interesting topic of research in bio-informatics. In previous methods,drugs were designed using only seven chemical components and were represented as a fixedlength
tree. But in reality, a drug contains many chemical groups collectively known as
pharmacophore. Moreover, the chemical length of the drug cannot be determined before
designing the drug.
In the present work, a Particle Swarm Optimization (PSO) based methodology has been
proposed to find out a suitable drug for a particular disease so that the drug-protein interaction
becomes stable. In the proposed algorithm, the drug is represented as a variable length tree and essential functional groups are arranged in different positions of that drug. Finally, the structure of the drug is obtained and its docking energy is minimized simultaneously. Also, the
orientation of chemical groups in the drug is tested so that it can bind to a particular active site of a target protein and the drug fits well inside the active site of target protein. Here, several inter-molecular forces have been considered for accuracy of the docking energy. Results showthat PSO performs better than the earlier methods.
Each and every biological function in living organism occurs due to protein-protein interactions. The
diseases are no exception to this. Identifying one or more proteins for a particular disease and then
designing a suitable chemical compound (which is known as drug or ligand) to destroy those proteins is a
challenging topic of research in computational biology. In earlier methods, drugs were designed using only
a few chemical components and were represented as a fixed-length tree. But in reality, a drug contains
many chemical groups collectively known as pharmacophore. Moreover, the chemical length of the drug
cannot be determined before designing that drug.
In the present work, a Particle Swarm Optimization (PSO) based methodology has been proposed to find
out a suitable drug for a particular disease so that the drug-target protein interaction energy becomes
minimum. In the proposed algorithm, the drug is represented as a variable length tree and essential
functional groups are arranged in different positions of that drug. Finally, the structure of the drug is
obtained and its docking energy is minimized simultaneously. Also, the orientation of chemical groups in
the drug is tested so that it can bind to a particular active site of a target protein and the drug fits well
inside the active site of target protein. Here, several inter-molecular forces have been considered for
accuracy of the docking energy. Results are demonstrated for three different target proteins both
numerically and pictorially. Results show that PSO performs better than the earlier methods.
IOSR Journal of Applied Chemistry (IOSR-JAC) is an open access international journal that provides rapid publication (within a month) of articles in all areas of applied chemistry and its applications. The journal welcomes publications of high quality papers on theoretical developments and practical applications in Chemical Science. Original research papers, state-of-the-art reviews, and high quality technical notes are invited for publications.
Cadd and molecular modeling for M.PharmShikha Popali
THE CADD IS FOR THE DRUG DEVELOPMENT THE DIFFERENT STRATEGIES ARE MENTIONED LIKE QSAR MOLECULAR DOCKING, THE DIFFERENT DIMNSIONAL FORMS OF QSAR , THE ADVANCE SAR of it.
COMPUTATIONAL MODELING OF DRUG DISPOSITION.pptxPoojaArya34
Computational modelling of drug disposition is the integral part of computer aided drug design. different kinds of tools being used in the prediction of drug disposition in human body. This topic in the CADD explains the details about the drug disposition, active transporters and tools.
Historically, drug discovery has focused almost exclusively on efficacy and selectivity against the biological target.
As a result, nearly half of drug candidates fail at phase II and phase III clinical trials because of undesirable drug pharmacokinetics properties, including absorption, distribution, metabolism, excretion, and toxicity (ADMET).
The pressure to control the escalating cost of new drug development has changed the paradigm since the mid-1990s. To reduce the attrition rate at more expensive later stages, in vitroevaluation of ADMET properties in the early phase of drug discovery has been widely adopted.Many high-throughput in vitro ADMET property screening assays have been developed and applied successfully .
For example, Caco-2 and MDCK cell monolayers are widely used to simulate membrane permeability as an in vitro estimation of in vivo absorption.
These in vitro results have enabled the training of in silico models, which could be applied to predict the ADMET properties of compounds even before they are synthesized.
Molecular Modeling of Metalloreductase STEAP2 Protein and Docking Interaction...BRNSS Publication Hub
This gene is an individual from the STEAP family and encodes a multipass film protein that confines to the Golgi complex, the plasma layer, and the vesicular cylindrical structures in the cytosol. A very comparative protein in mouse has both ferrireductase and cupric reductase action and invigorates the cell take-up of both iron and copper in vitro. Expanded transcriptional articulation of the human quality is related with prostate malignant growth movement. Substitute transcriptional graft variations, encoding distinctive isoforms, have been described. Therefore, in the present study, we generated a precise three-dimensional (3D) model of metalloreductase STEAP2 protein using MODELLER 9.21 and validated its structure using PROCHECK software. Modeled protein contains more than 94.5% of amino acids in core region. We interpreted the action of natural compounds docking against the modeled metalloreductase STEAP2 protein. Three compounds (ginkgetin, medicagenin, and erybraedin A) showed lower binding affinity values toward metalloreductase STEAP2 protein compared to mitoxantrone, abiraterone acetate, apalutamide, enzalutamide, and flutamide. Ginkgetin exhibited the lowest binding energy of −9.10 kcal/mol with interacting Trp212 and Thr210. All the 17 compounds showed excellent binding energies than standard drugs for the modeled metalloreductase STEAP2 protein. These computational studies can be helpful to discover novel drug candidates.
Call for Research Articles - 10th International Conference on Bioinformatics ...bioejjournal
10th International Conference on Bioinformatics & Biosciences (BIOS 2024) is a forum for presenting new advances and research results in the field of biology to increase the understanding of all biological process. The aim of this conference is to publish all the latest and outstanding research articles in all areas of bioinformatics and Biometrics. Researchers and scientists from the fields of biology, computer science, mathematics, statistics, and physics are invited to share their developments and new techniques in the fields of Biometrics and Bioinformatics. .
DE NOVO TRANSCRIPTOME ASSEMBLY OF SOLID SEQUENCING DATA IN CUCUMIS MELObioejjournal
As sequencing technologies progress, focus shifts towards solving bioinformatic challenges, of which
sequence read assembly is the first task. In the present study, we have carried out a comparison of two
assemblers (SeqMan and CLC) for transcriptome assembly, using a new dataset from Cucumis melo.
Between two assemblers SeqMan generated an excess of small, redundant contigs where as CLC generated
the least redundant assembly. Since different assemblers use different algorithms to build contigs, we
followed the merging of assemblies by CAP3 and found that the merged assembly is better than individual
assemblies and more consistent in the number and size of contigs. Combining the assemblies from different
programs gave a more credible final product, and therefore this approach is recommended for quantitative
output
Cloning and Extracellular Expression of Recombinant Tissue Plasminogen Activa...bioejjournal
Tissue plasminogen activator (tPA) has noteworthy application in treatment of acute myocardial
infarctions. This study focuses on expression of rt-PA using microbial systems in order to reduce cost
without compromising on quality as an alternative to commercial (rt-PA)produced by using mammalian
host systems. In the present study, Pichia pastoris X-33strain was used as a host with pICZαA expression
vector to obtain extracellular expression of full length tPA gene. Specific primers were designed in such a
way to get native tPA protein sequence in subsequent purification steps. Further, construct pICZαA-tPA
was developed and electroporated into host to achieve stablert-PA gene by achieving genome integration.
The transformants were screened for phenotypic characters.Mut+
phenotypic colony named Pichia tPA-3
showed expression of rt-PA at 66 kDa on SDS PAGE. Size Exclusion Chromatography (SEC) was
performed, resulting in product peak at same RT as reference standard. (alteplase).Cloning and expression
of rt-PA was successfully achieved in microbial system. Further process optimization at larger scales will
surely provide cost effective alternative to mammalian system forrt-PA production.
ANTIOXIDANT AND ANTIMICROBIAL ACTIVITIES OF ALGERIAN POPULUS NIGRA L. BUDS EX...bioejjournal
This study is part of a goal to investigate chemical composition, antibacterial, antifungal and antioxidant
activities of the flower buds extracts from the Algerian Polulus nigra L., which were collected from Djarifet
- mansourah at Tlemcen city in the West Northern of Algeria.
In organic extracts, tanins, flavonoïds, coumarins, alkaloids and terpenoïds were the principals secondary
metabolites identified from the flower buds of black poplar. Antibacterial and antifungal activities of
extracts were tested using agar-well diffusion method and micro-well determination of MIC assay against
eleven bacteria and two Candida species. It was found that extracts of black poplar buds exhibit
antibacterial and anticandidal activities with agar disk diffusion (7 to 43mm) and MIC methods (MIC=
90.33 µg/ml against several strains of bacteria and MIC=45.16 µg/ml against Candida albicans). The
antioxidant effect of hydroalcoholic extract was evaluated using DPPH and FRAP assays. It was showed
good and similar activity than ascorbic acid and BHA by DPPH method: IC50= 220µg/mL for
hydroethanol extract.
10th International Conference on Bioinformatics & Biosciences (BIOS 2024)bioejjournal
10th International Conference on Bioinformatics & Biosciences (BIOS 2024) is a forum for presenting new advances and research results in the field of biology to increase the understanding of all biological process. The aim of this conference is to publish all the latest and outstanding research articles in all areas of bioinformatics and Biometrics. Researchers and scientists from the fields of biology, computer science, mathematics, statistics, and physics are invited to share their developments and new techniques in the fields of Biometrics and Bioinformatics. .
Bioscience & Engineering: An International Journal (BIOEJ)bioejjournal
Bioscience & Engineering: An International Journal (BIOEJ) is a peer-reviewed, open access journal that addresses the impacts and challenges of Bioscience, Bioengineering and Applications. The journal documents practical and theoretical results which make a fundamental contribution for the development of Bioscience & Engineering.
LOW POWER CLASS AB SI POWER AMPLIFIER FOR WIRELESS MEDICAL SENSOR NETWORKbioejjournal
The objective of this research was to design a 2.4 GHz class AB Power Amplifier (PA), with 0.18um
Semiconductor Manufacturing International Corporation (SMIC) CMOS technology by using Cadence
software, for health care applications. The ultimate goal for such application is to minimize the trade-offs
between performance and cost, and between performance and low power consumption design. This paper
introduces the design of a 2.4GHz class AB power amplifier which consists of two stage amplifiers. This
power amplifier can transmit 10dBm output power to a 50Ω load. The power added efficiency is 7.5% at
1dB compression point and the power gain is 10dB, the total power consumption is 0.135W. The
performance of the power amplifier meets the specification requirements of the desired.
Bioscience & Engineering: An International Journal (BIOEJ)bioejjournal
Bioscience & Engineering: An International Journal (BIOEJ) is a peer-reviewed, open access journal that addresses the impacts and challenges of Bioscience, Bioengineering and Applications. The journal documents practical and theoretical results which make a fundamental contribution for the development of Bioscience & Engineering.
Phonocardiogram Based Diagnosis Using Machine Learning : Parametric Estimatio...bioejjournal
The heart sound signal, Phonocardiogram (PCG) is difficult to interpret even for experienced
cardiologists. Interpretation are very subjective depending on the hearing ability of the physician. mHealth
has been the adopted approach towards quick diagnosis using mobile devices. However, it has been
challenging due to the required high quality of data, high computation load, and high-power consumption.
The aim of this paper is to diagnose the heart condition based on Phonocardiogram analysis using
Machine Learning techniques assuming limited processing power to be encapsulated later in a mobile
device. The cardiovascular system is modelled in a transfer function to provide PCG signal recording as it
would be recorded at the wrist. The signal is, then, decomposed using filter bank and the analysed using
discriminant function. The results showed that PCG with a 19 dB Signal-to-Noise-Ratio can lead to 97.33%
successful diagnosis.
Call for Papers - Bioscience & Engineering: An International Journal (BIOEJ)bioejjournal
Bioscience & Engineering: An International Journal (BIOEJ) is a peer-reviewed, open access journal that addresses the impacts and challenges of Bioscience, Bioengineering and Applications. The journal documents practical and theoretical results which make a fundamental contribution for the development of Bioscience & Engineering.
NANO BIONIC SWIMMING ROBOTICS ANDAPPLICATIONS IN ENVIRONMENTALENGINEERINGbioejjournal
As microscopic swimmers survive in nature, they have evolved unique structures and swimmingpatterns under the water, which has special advantages. The movement of bacteria at lowReynolds number (Re) environment has aroused extensive research interest. The two typical
swimming methods of bacteria are introduced in this paper. Based on this, we are inspired to design the bionic robot on a micro-scale, which is an artificial
structure that imitates the external shape, movement principle and behavior mode of organisms innature. Compared with traditional robots, nano bionic robots are easier to miniaturize[1]. Theyalso have higher maneuverability so that they can move continuously and flexibly. We expect tosimulate its motion at low Reynolds number (Re) fluids and explore complex future applicationsin dif erent fields
Consistent Relationship of Both Watercontent and Activity With Maize Seed Qua...bioejjournal
Seed quality can be explained using a range of indices that are acceptable within the standards set by the
International Seed Testing Association. There is a need to improve existing models to explain the wellknown variations in seed quality within and between crop species. The objective of this study was to
determine the consistency of using grain water occurrence to explain seed quality in terms of viability and
vigour in maize (Zea mays L.). Four sites were used over two seasons to grow three cultivars in order to
monitor changes in water content, water activity, dry mass and total starch observed in different cob
sections (tip, medium and bottom) at 30, 60 and 90 days after pollination. Seed quality was determined
based on the germination and vigour of physiologically mature kernels. It is concluded that grains that
seed quality is linked to the water activity and position on the cob.
Next Generation Sequencing in Detecting Oral Cancer Due to Tobacco Consumptionbioejjournal
DNA sequence DNA Sequencing is the first step in establishing phylogenetic trees, protein structure
prediction, diagnosis of cancer, discovery of drugs and hence its importance cannot be underestimated.
DNA sequencing finds its use in the diagnosis of oral squamous cell carcinoma (OSCC). Oral Cancer is
the most common occurring malignancies in the world, especially in India where the prevalence for
smoking, Areca nut chewing coupled with a lifestyle that encourages these two activities as fashion are left
many people diagnosed with OSCC. Patients with this OSCC are more likely unaware of its side effects
and over time might suffer from facial deformity. The importance to understanding the symptoms,
prevention and treatment of oral cancer is very much essential today. In this paper, we looked at over 2000
odd papers published and look at the correlation between the next Generation DNA sequencing algorithms
(NGS) play an important role in diagnosis of OSCC. This is a further study on some of the papers which
have highlighted NGS role in OSCC Diagnosis. We did like to see a comprehensive review on the papers
published so far. In the discussion, we will see frequently mutated genes in the OSCC, recent discoveries
and OSCC treatment based on the findings.
Role of Computational Biology in Oral Sciencebioejjournal
DNA sequence Cigarette Smoking, Betel leaf chewing, and alcohol consumption are major cause of oral
cancer in Asia. The difficulty in quitting, coupled with patients’ economic conditions affects the inability to
get diagnosed early, driving death rate higher. There has been major advancement in molecular sciences,
computational biology, and other fields today, but we are not still able to pinpoint the causes of oral
cancer, also known as Squamous Cell Carcinoma (OSCC). Early detection leads to better survival rate,
therefore, education on yearly check-ups plays a vital role. Computational analysis at the genomic (DNA
sequence) can help patients with targeted cellular treatment and hopefully a cure. In this paper, we would
look at computation tools used in detecting OSCC and various analysis. Analysis includes detecting
abnormality in the cell and other molecular reactions which later morph into a cancerous cell. Later, we
investigate all computational tools or techniques from local and global sequence alignment, protein
structure, gene, functional structure analysis which help medical staff detect cancer, which in turn can help
with oral cancer treatment, prognosis and hopefully a cure.
NEXT GENERATION SEQUENCING IN DETECTING ORAL CANCER DUE TO TOBACCO CONSUMPTIONbioejjournal
DNA sequence DNA Sequencing is the first step in establishing phylogenetic trees, protein structure
prediction, diagnosis of cancer, discovery of drugs and hence its importance cannot be underestimated.
DNA sequencing finds its use in the diagnosis of oral squamous cell carcinoma (OSCC). Oral Cancer is
the most common occurring malignancies in the world, especially in India where the prevalence for
smoking, Areca nut chewing coupled with a lifestyle that encourages these two activities as fashion are left
many people diagnosed with OSCC. Patients with this OSCC are more likely unaware of its side effects
and over time might suffer from facial deformity. The importance to understanding the symptoms,
prevention and treatment of oral cancer is very much essential today. In this paper, we looked at over 2000
odd papers published and look at the correlation between the next Generation DNA sequencing algorithms
(NGS) play an important role in diagnosis of OSCC. This is a further study on some of the papers which
have highlighted NGS role in OSCC Diagnosis. We did like to see a comprehensive review on the papers
published so far. In the discussion, we will see frequently mutated genes in the OSCC, recent discoveries
and OSCC treatment based on the findings.
ROLE OF COMPUTATIONAL BIOLOGY IN ORAL SCIENCEbioejjournal
DNA sequence Cigarette Smoking, Betel leaf chewing, and alcohol consumption are major cause of oral
cancer in Asia. The difficulty in quitting, coupled with patients’ economic conditions affects the inability to
get diagnosed early, driving death rate higher. There has been major advancement in molecular sciences,
computational biology, and other fields today, but we are not still able to pinpoint the causes of oral
cancer, also known as Squamous Cell Carcinoma (OSCC). Early detection leads to better survival rate,
therefore, education on yearly check-ups plays a vital role. Computational analysis at the genomic (DNA
sequence) can help patients with targeted cellular treatment and hopefully a cure. In this paper, we would
look at computation tools used in detecting OSCC and various analysis. Analysis includes detecting
abnormality in the cell and other molecular reactions which later morph into a cancerous cell. Later, we
investigate all computational tools or techniques from local and global sequence alignment, protein
structure, gene, functional structure analysis which help medical staff detect cancer, which in turn can help
with oral cancer treatment, prognosis and hopefully a cure.
Statistical Based Media Optimization and Production of Clavulanic Acid By Sol...bioejjournal
Statistics based optimization, Plackett–Burman design (PBD) and response surface methodology
(RSM) were employed to screen and optimize the media components for the production of
clavulanic acid from Streptomyces clavuligerus MTCC 1142, using solid state fermentation. jackfruit
seed powder was used as both the solid support and carbon source for the growth of Streptomyces
clavuligerus MTCC 1142. Based on the positive influence of the Pareto chart obtained from PBD on
clavulanic acid production, five media components – yeast extract, beef extract, sucrose, malt extract
and ferric chloride were screened. Central composite design (CCD) was employed using these five
media components- yeast extract 2.5%, beef extract 0.5%, sucrose 2.5%, malt extract 0.25% and ferric
chloride nutritional factors at three levels, for further optimization, and the second order polynomial
equation was derived, based on the experimental data. Response surface methodology showed that
the concentrations of yeast extract 2.5%, beef extract 0.5%, sucrose 2.5%, malt extract 0.25% and ferric
chloride 2.5% were the optimal levels for maximal clavulanic acid production (19.37 mg /gds) which
were validated through experiments.
A New Low-Complexity Algorithm for the Pulse Transit Time Evaluationbioejjournal
The pulse transit time (PTT) is a physiological parameter commonly derived from Electrocardiogram
(ECG) and Photoplethysmogram (PPG) signal. It is defined as the time taken for the arterial pulse to
travel from the heart to a peripheral site, and can be used as a direct indicator of Cardiovascular Diseases
(CVD). In this study, we propose a new low-complexity algorithm for the (PTT) estimation. The (PTT) is
calculated as the interval between the peak of the ECG R-wave and a time point on the PPG. We
considered a dataset of 37 subjects containing a simultaneous recording of the (ECG) and the (PPG). The
computation of the (PTT) consists of detecting the peak and foot points of a (PPG) and the R peak of the
(ECG) signal. Our algorithm is improved by a temporal analysis by windowing. The results obtained are
promising. The average sensitivity (SEN) and accuracy (ACC) obtained are respectively (97.5%, and
96.82%) for the detection of R peaks and (97.77%, and 97.64%) for the detection of PPG peaks. The
sensitivity (SEN) and accuracy (ACC) of the foot (PPG) detection were 98.33% and 94.14%.
ANTIOXIDANT AND ANTIMICROBIAL ACTIVITIES OF ALGERIAN POPULUS NIGRA L. BUDS EX...bioejjournal
This study is part of a goal to investigate chemical composition, antibacterial, antifungal and antioxidant
activities of the flower buds extracts from the Algerian Polulus nigra L., which were collected from Djarifet
- mansourah at Tlemcen city in the West Northern of Algeria.
In organic extracts, tanins, flavonoïds, coumarins, alkaloids and terpenoïds were the principals secondary
metabolites identified from the flower buds of black poplar. Antibacterial and antifungal activities of
extracts were tested using agar-well diffusion method and micro-well determination of MIC assay against
eleven bacteria and two Candida species. It was found that extracts of black poplar buds exhibit
antibacterial and anticandidal activities with agar disk diffusion (7 to 43mm) and MIC methods (MIC=
90.33 µg/ml against several strains of bacteria and MIC=45.16 µg/ml against Candida albicans). The
antioxidant effect of hydroalcoholic extract was evaluated using DPPH and FRAP assays. It was showed
good and similar activity than ascorbic acid and BHA by DPPH method: IC50= 220µg/mL for
hydroethanol extract.
NEW SEQUENCE ALIGNMENT ALGORITHM USING AI RULES AND DYNAMIC SEEDSbioejjournal
DNA sequence alignment is important today as it is usually the first step in finding gene mutation,
evolutionary similarities, protein structure, drug development and cancer treatment. Covid-19 is one
recent example. There are many sequencing algorithms developed over the past decades but the sequence
alignment using expert systems is quite new. To find DNA sequence alignment, dynamic programming was
used initially. Later faster algorithms used small DNA sequence length of fixed size to find regions of
similarity, and then build the final alignment using these regions. Such systems were not sensitive but were
fast. To improve the sensitivity, we propose a new algorithm which is based on finding maximal matches
between two sequences, find seeds between them, employ rules to find more seeds of varying length, and
then employ a new stitching algorithm, and weighted seeds to solve the problem.
Cosmetic shop management system project report.pdfKamal Acharya
Buying new cosmetic products is difficult. It can even be scary for those who have sensitive skin and are prone to skin trouble. The information needed to alleviate this problem is on the back of each product, but it's thought to interpret those ingredient lists unless you have a background in chemistry.
Instead of buying and hoping for the best, we can use data science to help us predict which products may be good fits for us. It includes various function programs to do the above mentioned tasks.
Data file handling has been effectively used in the program.
The automated cosmetic shop management system should deal with the automation of general workflow and administration process of the shop. The main processes of the system focus on customer's request where the system is able to search the most appropriate products and deliver it to the customers. It should help the employees to quickly identify the list of cosmetic product that have reached the minimum quantity and also keep a track of expired date for each cosmetic product. It should help the employees to find the rack number in which the product is placed.It is also Faster and more efficient way.
Immunizing Image Classifiers Against Localized Adversary Attacksgerogepatton
This paper addresses the vulnerability of deep learning models, particularly convolutional neural networks
(CNN)s, to adversarial attacks and presents a proactive training technique designed to counter them. We
introduce a novel volumization algorithm, which transforms 2D images into 3D volumetric representations.
When combined with 3D convolution and deep curriculum learning optimization (CLO), itsignificantly improves
the immunity of models against localized universal attacks by up to 40%. We evaluate our proposed approach
using contemporary CNN architectures and the modified Canadian Institute for Advanced Research (CIFAR-10
and CIFAR-100) and ImageNet Large Scale Visual Recognition Challenge (ILSVRC12) datasets, showcasing
accuracy improvements over previous techniques. The results indicate that the combination of the volumetric
input and curriculum learning holds significant promise for mitigating adversarial attacks without necessitating
adversary training.
Overview of the fundamental roles in Hydropower generation and the components involved in wider Electrical Engineering.
This paper presents the design and construction of hydroelectric dams from the hydrologist’s survey of the valley before construction, all aspects and involved disciplines, fluid dynamics, structural engineering, generation and mains frequency regulation to the very transmission of power through the network in the United Kingdom.
Author: Robbie Edward Sayers
Collaborators and co editors: Charlie Sims and Connor Healey.
(C) 2024 Robbie E. Sayers
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About
Indigenized remote control interface card suitable for MAFI system CCR equipment. Compatible for IDM8000 CCR. Backplane mounted serial and TCP/Ethernet communication module for CCR remote access. IDM 8000 CCR remote control on serial and TCP protocol.
• Remote control: Parallel or serial interface.
• Compatible with MAFI CCR system.
• Compatible with IDM8000 CCR.
• Compatible with Backplane mount serial communication.
• Compatible with commercial and Defence aviation CCR system.
• Remote control system for accessing CCR and allied system over serial or TCP.
• Indigenized local Support/presence in India.
• Easy in configuration using DIP switches.
Technical Specifications
Indigenized remote control interface card suitable for MAFI system CCR equipment. Compatible for IDM8000 CCR. Backplane mounted serial and TCP/Ethernet communication module for CCR remote access. IDM 8000 CCR remote control on serial and TCP protocol.
Key Features
Indigenized remote control interface card suitable for MAFI system CCR equipment. Compatible for IDM8000 CCR. Backplane mounted serial and TCP/Ethernet communication module for CCR remote access. IDM 8000 CCR remote control on serial and TCP protocol.
• Remote control: Parallel or serial interface
• Compatible with MAFI CCR system
• Copatiable with IDM8000 CCR
• Compatible with Backplane mount serial communication.
• Compatible with commercial and Defence aviation CCR system.
• Remote control system for accessing CCR and allied system over serial or TCP.
• Indigenized local Support/presence in India.
Application
• Remote control: Parallel or serial interface.
• Compatible with MAFI CCR system.
• Compatible with IDM8000 CCR.
• Compatible with Backplane mount serial communication.
• Compatible with commercial and Defence aviation CCR system.
• Remote control system for accessing CCR and allied system over serial or TCP.
• Indigenized local Support/presence in India.
• Easy in configuration using DIP switches.
Qsar studies on gallic acid derivatives and molecular docking studies of bace1 enzyme a potent
1. Bioscience & Engineering: An International Journal (BIOEJ), Vol.1, No.1, July 2014
11
Qsar Studies on Gallic Acid Derivatives and
Molecular Docking Studies of Bace1 Enzyme – A
Potent Target of Alzheimer Disease.
KrishnaKant Gupta1
1
PhD Research Scholar, Center for Bioinformatics, Pondicherry University, Pondicherry,
India,
Abstract
It is reported that Alzheimer disease is linked with hypertension, diabetes type 2 and high cholesterolemia.
The underlying genetic cause relating these diseases are not well studied clinically. But it has been widely
accepted that beta secretase (BACE1) is the main culprit of causing Alzheimer disease. This enzyme comes
under peptidase A1 family. In the present work, ligand based and structure based drug designing have been
reported. QSAR studies were done using 21 gallic acid derivatives dataset to develop good predictive
model in order to predict biological activity and certain descriptors was reported to further enhance the
analgesic activity of gallic acid derivatives. Molecular docking studies were performed in order to find
structure based drug design. Two natural gallic acid derivative have been repoted as a potent inhibitor to
beta secretase enzyme.
Keywords: Alzheimer Disease, beta secretase, QSAR, Molecular docking, Ligands, inhibitor.
1. Introduction
Millions of peoples worldwide are affected by this devastating disease i.e., Alzheimer Disease
(AD). The hallmark of AD brain includes the presence of amyloid plaques, neurofibrillary
tangles, loss of neurons and synapses, and oxidative damage. Amyloid precursor protein (APP) is
embedded in cell membrane, the barrier that encloses the cell. There are number of APP snipping
enzymes. Alpha secretase, beta-secretase, and gamma-secretase are main APP snipping peptidase.
These enzymes were discovered in 1999 and 2000. [1]
APP processing can follow one of two pathways that have very different consequences for the
cell. In the non-harmful pathway, alpha-secretase snip the APP molecule and releases from the
neuron a fragment called sAPPα, which has been reported for promoting neuronal growth and
survival. The remaining APP fragment is then cleaved by gamma-secretase at the end of the beta-
amyloid segment. The smaller of the resulting fragments also is released into the space outside
the neuron, while the larger fragment remains within the neuron and interacts with factors in the
nucleus. [2]
It is experimentally reported that oxidative stress results in increase in the activity of Beta
Secretase (BACE1) through activation of the PKR-eIF2α pathway. In the harmful pathway, beta-
secretase first snip the APP molecule, releasing sAPPβ from the cell. sAPPβ act as a ligand for
DR6 (Death protein) – as is a fragment of its close relative, APLP2 - that triggers degeneration of
cell bodies via caspase-3 and axons via caspase-6 [3]. Similarly as in case of alpha secretase
2. Bioscience & Engineering: An International Journal (BIOEJ), Vol.1, No.1, July 2014
12
pathway, gamma-secretase then cuts the resulting APP fragment, the beta amyloid peptide is
released into the space outside the neuron and begins to stick to other beta-amyloid peptides.
These small, soluble aggregates of two, three, four, or even up to a dozen beta-amyloid peptides
are called oligomers. Size dependent oligomers may be responsible for reacting with receptors on
neighboring cells and synapses, affecting their ability to function. It is likely that some oligomers
are cleared from the brain. Those that cannot be cleared clump together with more beta-amyloid
peptides. As the process continues, oligomers grow larger, becoming entities called protofibrils
and fibrils.
What is QSAR?
QSAR is a study of empirical relationships between structure and property. When considerable
biological information is not available then QSAR study shed light on it . Quantitative
structure-activity relationships (QSAR) are methods which correlate molecular structure
(descriptors) to some kind of in vitro or in vivo biological property. When this approach is
applied to modelling of toxicological data, it is termed quantitative structure —toxicity
relationships (QSTR).When applied to modelling of physicochemical properties it is called
quantitative structure — property relationships (QSPR).[4]
QSAR in particular, first developed by Hansch and Fujita 40 years ago, has been invaluable for
understanding drug structure —activity relationships for lead discovery and optimisation.
What is Molecular docking?
Docking is a method which finds the preferred orientation of one molecule to a second when
bound to each other to form a stable complex. [5] Algorithm of the search space and scoring
function is the basis of predicting any binding affinity between two molecules.
In the present work, ligand based and structure based drug designing have been reported. QSAR
studies were done using 21 gallic acid derivatives dataset to develop good predictive model in
order to predict biological activity and certain descriptors was reported to further enhance the
analgesic activity of gallic acid derivatives. Molecular docking studies were performed in order to
find structure based drug design. Two natural gallic acid derivative have been repoted as a potent
inhibitor to beta secretase enzyme.
2. Material and Methodology
2.1 Dataset retrieval for QSAR model building:
49 compounds with their biological activity dataset were taken from the paper entitled
“Structure–activity relationships for the analgesic activity of gallicacid derivatives.” [6]
2.2 QSAR model building:
QSAR model were build using Sarchitect software. [7] The Multiple linear regressions were used
to build QSAR model. The brief steps considered for model building are following:
3. Bioscience & Engineering: An International Journal (BIOEJ), Vol.1, No.1, July 2014
13
Optimization of structure
Structure optimization is an important step as descriptors calculation and their accuracy is largely
affected by the structure of molecules. Geometrical and conformational descriptors depend on
structural features such as bond length, bond angle and position of atoms in space to provide
confirmation.
Calculation of Descriptors
Molecular descriptors are numerical values obtained by the quantification of various structural
and physicochemical characteristics of the molecule. It is envisaged that molecular descriptors
quantify these attributes so as to determine the behavior of the molecule and the way the
molecule interacts with a physiological system. Since the exact mechanism of drug activity is
unknown in many cases, it is desirable to start with descriptors spanning as many attributes of the
molecules as possible and then assess their ability to predict the desired activity/property. Some
programs compute over a thousand descriptors covering constitutional, topological and
conformational spaces of compounds. Descriptors for present dataset were calculated using E-
Dragon [8] which an online tool is provided by Virtual Chemistry Laboratories. Parameter Client
is the interface for the E-Dragon. This program makes all classes of descriptors available
according to their categories. Topological, geometrical, Constitutional, Conformational,
Connectivity based etc. can be easily calculated using this program. Its offline version DRAGON
can also be used to calculate descriptors but only for the molecules having atoms less than 50 and
number of descriptors are also less as compare to E-Dragon.
Pruning of Descriptors
The Prune Descriptors Wizard drops descriptors with low variance and handles missing values.
This step was used to removes all descriptors for which either Standard Deviation or Coefficient
of variance were less than the specified cutoff.
Statistical Tests/Correlation
This step ranks the descriptors in the order of their relevance to the endpoint (Biological activity)
value. Ensure that the appropriate dataset is chosen in the Navigator. If the endpoint is
Categorical, ranking is done using Kruskal-Wallis (uses H-statistic) and if the endpoint value is
Continuous, ranking is based on Correlation (uses Pearson Correlation Coefficient.
Forward/Backward Selection
The most straightforward search strategies are based on stepwise addition or elimination of
descriptors. A sequential selection wrapper proceeds by adding or removing features from the
current set to form a new candidate. This was then evaluated using some validation metric (n-
fold or leave-one-out accuracy) and if it is superior then it replaces the current optimal set and the
algorithm continues. The process terminates when no more valid operations (addition/removal)
can be performed or if no candidate feature exceeds the performance of its predecessor. Forward
Selection and Backward Elimination select the most relevant descriptors based on stepwise
addition or elimination of features. In forward selection, variables are progressively incorporated
into larger and larger subsets, whereas in backward elimination one starts with the set of all
4. Bioscience & Engineering: An International Journal (BIOEJ), Vol.1, No.1, July 2014
14
variables and progressively eliminates the least promising ones. Both methods yield nested
subsets of variables.
Generation of Models for Dataset.
The best models out of all available models can be chosen after study of their statistical
parameters like regression coefficient r2
, adjusted r2
standard error and F-state t- test etc. a model
with r2
values higher than 0.499 can be selected for prediction of activity in QSAR.
2.3 Docking studies
Downloading crystal structure of Beta secretase and active site residues analysis:
The crystal structure of beta secretase (2HIZ) was downloaded from Protein data bank (PDB)
[9]. This structure was subjected to active site residues analysis. Both Prediction based and
literature based proof was considered to find the most potent domain of this A1 peptidase.
Molegro virtual docker [10] was used to predict active sites in beta secretase and an article
entitled “Crystallization and structure determination of glycosylated human beta secretase, an
enzyme implicated in alzheimer's disease." [ref] was used to verify the predicted active site
cavity.
Molecular docking studies and interaction analysis:
Molegro Virtual docker was used for molecular docking studies. All the ligands from gallic acid
deivatives that were used for QSAR studies, were used to screen the selected active site of beta
secretase. Based on RMSD, Moldock score and three types of interaction analysis i.e., Hydrogen
bond, electrostatic interaction and hydrophobic interaction, the affinity of proposed ligands were
ranked and top two ligands were proposed as a potent and natural inhibitor for beta secretase
enzyme.
3. Result
Out of 49 derivatives, only 21 compounds were considered for QSAR model building. (Table 1)
All compounds were considered as training set. No test set were assigned.
Table1: Structure-Activity of 21 gallic acid derivatives
Compound Structure
(gallic acid derivatives)
Analgesic
Activity(MI
CROMOL/K
G)
A(1) O
O O
O O
HH
H
H
H
H
30.4
5. Bioscience & Engineering: An International Journal (BIOEJ), Vol.1, No.1, July 2014
15
B(2) O
O O
O O
HH
H
H
H
H
H
H
H
H
H
H
39.48
C(3)
O
Cl
O
O O
O
HH
H
HH
H
H
H
H
39.26
D(4)
O O
Br
O
O O
HH
H
HH
H
H
H
H
17.51
E(5) HO
OH
OH
O O
N
O O
17.96
F(6)
O
O
O
O H
H
H
H
H
H
H
H
H
H
H
H
H
H
31.16
G(7)
O O
O
O O
HH H
H
HH
H H
H
H
H
H
H
H
20.15
6. Bioscience & Engineering: An International Journal (BIOEJ), Vol.1, No.1, July 2014
16
H(8)
O O
Cl
O
O O
HH H
H
H
H
H H
H
H
H
21.05
I(9)
O O
Cl
O
O
O
HH H
H
HH
H H
H
H
H
17.62
J(10)
O O
B r
O
O
O
HH H
H
H
H
H H
H
H
H
12.62
K(11)
O
O
O
O
O
H
H
H
H
H
H
H
H
H
H
H
H
H H
H H
37.87
L(12)
O
O
O
N
O
O
HH
H
H
H
H
H
23.6
M(13) O
O O
O N
HH
H
H
H
H
H
H
H
H
H
27.79
7. Bioscience & Engineering: An International Journal (BIOEJ), Vol.1, No.1, July 2014
17
N(14)
O N
O
O
O
HH
H
H
H
H
H
H
H H
H
H
H
15.2
O(15)
O
O N
O
O
O
HH
H
HH
H
H
H
H
H
H
H
H
29.17
P(16)
O N
O
O
O
O
HH
H
H
H
H
H
H
H
H
H
H
H
17.16
Q(17)
O O
I
O
O N
O
HH
H
H
H
H
H
H
H
H
H
H
H
H
11.66
R(18)
Br
O N
O
O O
HH
H
HH
H
H
H
H
H
11.46
8. Bioscience & Engineering: An International Journal (BIOEJ), Vol.1, No.1, July 2014
18
S(19)
Br
O N
O
O
O
HH
H
H
H
H
H
H
H
H
11.24
T(20)
N
N
O O
O
O
O
O
HH
H
HH
H
H
H
H
H
14.28
U(21)
O
O
O
O
O
O
O O
O
HH
H
HH
H
H
H
H
H
14.23
The following descriptors were best correlating with biological activity:
[H1e] - H autocorrelation of lag 1 weighted by atomic Sanderson electronegativities.
[RDF080m] -Radial Distribution Function - 8 weighted by atomic masses.
[H6m] -H autocorrelation of lag 6 weighted by atomic masses.
[GGI7] - topological charge index of order 7.
All these descriptors are 3D descriptors (such as, for example, 3D-MoRSE descriptors, WHIM
descriptors, GETAWAY descriptors, quantum-chemical descriptors, size, steric, surface and
volume descriptors)
On considering all these four descriptors, QSAR model with combination of H1e, RDF080m and
H6m were giving best model to predict biological activity of other gallic acid derivatives. On the
other side, the combination of addition of GG17 was adding to the predictive ability of QSAR
model, Therefore Two model were built with 3 and 4 descriptors combination.
9. Bioscience & Engineering: An International Journal (BIOEJ), Vol.1, No.1, Ju
QSAR Model with three best correlated descriptors (Third model):
ID50 (MICROMOL/KG) =138.228 -
+4.932(±0.570) (RDF080m) +9.174(±2.264) (H6m)
N=21 R2
=0.822 R2
A=0.799 S.E. =4.29 F=26.25
Cross Validated R2
=0.678
Table 2: Regression table for third model
The graph (Figure 1) is linear and not scattered; it implied the power of prediction is
good.
Figure 1: Graph showing third model predictive ability.
Leverage status is OK for most of the predictions
ng: An International Journal (BIOEJ), Vol.1, No.1, July 2014
QSAR Model with three best correlated descriptors (Third model):
-56.266(±7.811)(H1e)
+4.932(±0.570) (RDF080m) +9.174(±2.264) (H6m)
A=0.799 S.E. =4.29 F=26.25
Table 2: Regression table for third model
is linear and not scattered; it implied the power of prediction is
Figure 1: Graph showing third model predictive ability.
Leverage status is OK for most of the predictions. (Table 3)
2014
19
is linear and not scattered; it implied the power of prediction is
10. Bioscience & Engineering: An International Journal (BIOEJ), Vol.1, No.1, Ju
Table3: Validation: MLR Diagnostics of third model
QSAR Model with four best correlated descriptors (fourth model):
ID50 (MICROMOL/KG) =101.544 -
+5.609(±0.570) (RDF080m) +11.366(±1.931) (H6m)
N=21 R2
=0.893 R2
A=0.866 S.E. =3.436 F=33.450
Cross Validated R2
=0.826
Table 4: Regression table for third model
ng: An International Journal (BIOEJ), Vol.1, No.1, July 2014
Table3: Validation: MLR Diagnostics of third model
QSAR Model with four best correlated descriptors (fourth model):
-35.452(±8.940)(H1e)
+5.609(±0.570) (RDF080m) +11.366(±1.931) (H6m)-48.907(±15.029) (GGI7)
A=0.866 S.E. =3.436 F=33.450
Table 4: Regression table for third model
2014
20
11. Bioscience & Engineering: An International Journal (BIOEJ), Vol.1, No.1, Ju
The graph (Figure 2) is linear and not scattered; it implied the power of prediction is good
compared to figure 1.
Figure 2: Graph showing fourth model predictive ability.
In fourth model also Leverage status is OK for most of the predictions.
Table5: Validation: MLR Diagnostics of fourth model
DOCKING RESULTS:
Active site Residues with 10 angstrom of inhibitor binding site from beta secretase
2HIZ) are following:
ARG 7 TYR 71 LEU 121 THR 232 GLY 8 THR 72 ALA 122 ASN 233 LYS 9 GLN
123 LEU 234 SER 10 GLY 74 ALA 124 ARG 235 GLY 11 LYS 75 GLU 125 ARG 307 GLN 12
TRP 76 ILE 126 PHE 322 GLY 13 GLU 77 ALA 127 ALA 323 TYR 14 ILE 102 ARG 128 ILE
ng: An International Journal (BIOEJ), Vol.1, No.1, July 2014
is linear and not scattered; it implied the power of prediction is good
Figure 2: Graph showing fourth model predictive ability.
In fourth model also Leverage status is OK for most of the predictions. (Table 5)
Table5: Validation: MLR Diagnostics of fourth model
Active site Residues with 10 angstrom of inhibitor binding site from beta secretase
ARG 7 TYR 71 LEU 121 THR 232 GLY 8 THR 72 ALA 122 ASN 233 LYS 9 GLN
123 LEU 234 SER 10 GLY 74 ALA 124 ARG 235 GLY 11 LYS 75 GLU 125 ARG 307 GLN 12
TRP 76 ILE 126 PHE 322 GLY 13 GLU 77 ALA 127 ALA 323 TYR 14 ILE 102 ARG 128 ILE
2014
21
is linear and not scattered; it implied the power of prediction is good as
(Table 5)
Active site Residues with 10 angstrom of inhibitor binding site from beta secretase (PDBID:
ARG 7 TYR 71 LEU 121 THR 232 GLY 8 THR 72 ALA 122 ASN 233 LYS 9 GLN 73 TYR
123 LEU 234 SER 10 GLY 74 ALA 124 ARG 235 GLY 11 LYS 75 GLU 125 ARG 307 GLN 12
TRP 76 ILE 126 PHE 322 GLY 13 GLU 77 ALA 127 ALA 323 TYR 14 ILE 102 ARG 128 ILE
12. Bioscience & Engineering: An International Journal (BIOEJ), Vol.1, No.1, Ju
324 TYR 15 SER 105 PRO 129 SER 325 ILE 29 ASP 106 LEU 154 GLN 326 LEU 30 LYS 107
TRP 197 SER 327 VAL 31 PHE 108 TYR 198 SER 328 ASP 32 PHE 109 TYR 199
THR 33 ILE 110 ASP 223 GLY 330 GLY 34 ASN 111 LYS 224 THR 331 SER 35 SER 113
SER 225 VAL 332 SER 36 TRP 115 ILE 226 MET 333 ASN 37 GLU 116 VAL 227 GLY 334
ALA 39 GLY 117 ASP 228 ALA 335
GLY 230 MET 338 PRO 70 GLY 120 THR 231 GLU 339
All the 21 ligands were checked for scoring function and space search in terms of MDS and
RMSD respectively. Least MDS with less RMSD is supposed to be good for
represents the number of rotation a ligand can do
Table6: RMSD, MDS and torsion of 21 ligands
BEST MOLECULES:
Table7: RMSD, MDS and torsion of best 5 ligands
ng: An International Journal (BIOEJ), Vol.1, No.1, July 2014
324 TYR 15 SER 105 PRO 129 SER 325 ILE 29 ASP 106 LEU 154 GLN 326 LEU 30 LYS 107
SER 327 VAL 31 PHE 108 TYR 198 SER 328 ASP 32 PHE 109 TYR 199
THR 33 ILE 110 ASP 223 GLY 330 GLY 34 ASN 111 LYS 224 THR 331 SER 35 SER 113
SER 225 VAL 332 SER 36 TRP 115 ILE 226 MET 333 ASN 37 GLU 116 VAL 227 GLY 334
ALA 39 GLY 117 ASP 228 ALA 335 TYR 68 ILE 118 SER 229 VAL 336 VAL 69 LEU 119
GLY 230 MET 338 PRO 70 GLY 120 THR 231 GLU 339
All the 21 ligands were checked for scoring function and space search in terms of MDS and
RMSD respectively. Least MDS with less RMSD is supposed to be good for docking. Torsion
represents the number of rotation a ligand can do. (Table 6)
Table6: RMSD, MDS and torsion of 21 ligands
Table7: RMSD, MDS and torsion of best 5 ligands
2014
22
324 TYR 15 SER 105 PRO 129 SER 325 ILE 29 ASP 106 LEU 154 GLN 326 LEU 30 LYS 107
SER 327 VAL 31 PHE 108 TYR 198 SER 328 ASP 32 PHE 109 TYR 199 THR 329
THR 33 ILE 110 ASP 223 GLY 330 GLY 34 ASN 111 LYS 224 THR 331 SER 35 SER 113
SER 225 VAL 332 SER 36 TRP 115 ILE 226 MET 333 ASN 37 GLU 116 VAL 227 GLY 334
TYR 68 ILE 118 SER 229 VAL 336 VAL 69 LEU 119
All the 21 ligands were checked for scoring function and space search in terms of MDS and
docking. Torsion
13. Bioscience & Engineering: An International Journal (BIOEJ), Vol.1, No.1, Ju
Based on Least energy and less RMSD, two molecules was proposed to be the most potent
inhibitor of beta secretase enzyme. Molecule B and Molecule C must be checked preclinically
and clinically to support this work.
Table8: RMSD, MDS and torsio
POSES AND INTERACTIONS:
Hydrogen bond, Electrostatic and Hydrophobic interactions are shown in
Figure4: Electrostatic interaction (ligand B
ng: An International Journal (BIOEJ), Vol.1, No.1, July 2014
Based on Least energy and less RMSD, two molecules was proposed to be the most potent
inhibitor of beta secretase enzyme. Molecule B and Molecule C must be checked preclinically
and clinically to support this work. ( Table 8)
Table8: RMSD, MDS and torsion of best two ligands
Hydrogen bond, Electrostatic and Hydrophobic interactions are shown in Fig3-fig8.
Figure3: H-bond (ligand B-2HIZ)
Figure4: Electrostatic interaction (ligand B-2HIZ)
2014
23
Based on Least energy and less RMSD, two molecules was proposed to be the most potent
inhibitor of beta secretase enzyme. Molecule B and Molecule C must be checked preclinically
14. Bioscience & Engineering: An International Journal (BIOEJ), Vol.1, No.1, July 2014
24
Figure5: Hydrophobic interaction (ligand B-2HIZ)
Figure6: H-bond (ligand C-2HIZ)
15. Bioscience & Engineering: An International Journal (BIOEJ), Vol.1, No.1, July 2014
25
Figure7: Electrostatic interaction (ligand C-2HIZ)
Figure8: Hydrophobic interaction (ligand C-2HIZ)
4. Discussion
All the models from univaraint to tetravariable descriptors with their corresponding regression
coefficients r2
and adjusted r2
, standard error along with their F values etc. are given in table.
Results show progressive improvement in the r2
and decrease in the standard error. This indicates
addition of another descriptor to each model brings positive effect in the modeling criteria.
As the best two models of Gallic acid derivative’s activity show high values of r2
0.822, and
0.893 respectively. Thus both models should be used for prediction of activity in this QSAR
studies. Each model is studied with taking account on their F value, t- test, and over most errors
for each coefficient used in the model. Hence finally we have chosen both models with
16. Bioscience & Engineering: An International Journal (BIOEJ), Vol.1, No.1, July 2014
26
descriptors 3 and 4 for the QSAR of Gallic acid derivatives to predict their biological activity as
shown in table.
Statistically both models are accepted as they satisfy all the parametric requirements for approval.
As described earlier these models have got highest r2
and lowest standard error. F value
represents the quality of whole model and it is highest when compared to all models. In both
equations it is clear that each coefficient is larger enough to its error to avoid the chances of
withdrawal of this model. Using this model the activity has been predicted and shown in tables
above. Present QSAR work concludes important criteria for the Gallic acid derivatives as
inhibitors with respect to the structure affecting their ID50 activity to inhibit the BACE-1 enzyme
which is a prime target for Alzheimer. Lower activity of established drugs form market and
higher side effect profile is considered the base of search of new candidates of desired activity
with lower side effect profile. Thereafter search of lead molecule for BACE-1 Inhibition is in
progress and many research groups have made it target of their work. Organic synthesis of
molecules and their preclinical testing bears high cost on economy of pharmaceutical industries.
QSAR studies have always been used by the organic synthesis groups to converge the search of
lead molecules as it describes structural features required for increasing activity or decreasing it.
Present work has explained the role of different groups and their contribution towards ID50
activity. Researchers synthesizing new derivatives of Gallic acid derivatives may use the
information from this work and can work more efficiently and faster the rate of search inhibitors
for BACE-1.
3D Structure of Beta Secretase Enzyme (PDB ID 2HIZ) was chosen for carrying out docking
studies. A considerable part of population is suffering from Alzheimer and its associated
disorders. Present work is an effort to find better BACE-1 Inhibitors, as established drugs for it
show lower activity or higher side effects. We have selected a set of 21 molecules which were
being used in QSAR studies as Gallic acid derivatives. Docking studies have been an important
key step in screening of large data to an active molecule, it also enables us to calculate the
interactions out of hydrogen bonding, electrostatics and hydrophobic interactions. Docking
accuracy and output of result largely depends on input parameters and is finally decided by
RMSD value for the particular candidate. To date there are many docking software present in
chemoinformatics community, Such as FlexX, Glide, GOLD, Molegro Virtual Docker. Every
Docking tool uses different algorithms for the calculation of interactions and Scoring. Present
work output contains best 5 candidates out of 21 molecules; showing appreciable interactions
which are listed above in table. Their hydrogen bond, electrostatic and hydrophobic interactions
are also shown in diagrams separately. Best candidate obtained in present work is B with RMSD
value of 0.195 and score of 117.957. This candidate also shows appreciable interaction as
compared to others and amino acids residues present around it find reasonable interactions. The
next molecule of favourable activity found is C with RMSD value 0.382 and score 112.62. Both
the above molecules are newer than others and showing good possibilities of inhibition of the
protein. Following to this molecule there are other 3 molecules showing good RMSD and
SCORE they are given in table with their RMSD and corresponding SCORE. Thus these two
molecules with structure B and C can be further analyzed using ADMET studies, as these two
shows favourable docking capability to protein. This work confines to only docking studies and
further studies might favour their ability to inhibit the protein to significance concentrations.
Present work can be considered as the first steps towards efforts to find inhibitors for protein
BACE-1. Finally this inhibition can provide better health to human being.
17. Bioscience & Engineering: An International Journal (BIOEJ), Vol.1, No.1, July 2014
27
5. CONCLUSIONS
As per QSAR model, Researchers synthesizing new derivatives of Gallic acid derivatives may
use the information from this work and can work more efficiently and faster the rate of search
inhibitors for BACE-1.
Present work can be considered as the first steps towards efforts to find inhibitors for protein
BACE-1. Finally this inhibition can provide better health to human being.
ACKNOWLEDGEMENT
This work has been done in Eminent Bioscience, Indore, Madhya Pradesh, INDIA; under the
guidance of Dr. Mukesh yadav and Dr. Anuraj Nayarisseri. I am very thankful to both of them
for their support and good guidance.
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BIOGRAPHIES
Krishna Kant Gupta is pursuing PhD in Bioinformatics from Center for Bioinformatics,
Pondicherry University. He received his M.Sc. in Bioinformatics at the Devi Ahilya
University, Indore. He is a 2012 passout student at the School of Biotechnology and
Bioinformatics subcenter. He is Research trainee at Nthrys Biotech Labs. His research
interests include computer aided drug designing, molecular docking studies, protein-
protein interaction, epitope design. He is author of a great deal of research studies
published at national and international journals.