Amit Kumar Banerjee

Publications

• Analyzing a Potential Drug Target N-Myristoyltransferase of Plasmodium falciparum Through In Silico Approaches.

  Amit Kumar Banerjee, Neelima Arora, Usn Murty

  Journal of global infectious diseases. 01/2012; 4(1):43-54.

  Despite concerted global efforts to combat malaria, malaria elimination is still a remote dream. Fast evolution rate of malarial parasite along with its ability to respond quickly to any drug resulting in partial or complete resistance has been a cause of concern among researcher communities. Molecu... [more] Despite concerted global efforts to combat malaria, malaria elimination is still a remote dream. Fast evolution rate of malarial parasite along with its ability to respond quickly to any drug resulting in partial or complete resistance has been a cause of concern among researcher communities. Molecular modeling approach was adopted to gain insight about the structure and various analyses were performed. Modeller 9v3, Protparam, Protscale, MEME, NAMD and other tools were employed for this study. PROCHECK and other tools were used for stereo-chemical quality evaluation. It was observed during the course of study that this protein contains 32.2% of aliphatic amino acids among which Leucine (9.5%) is predominant. Theoretical pI of 8.39 identified the protein as basic in nature and most of the amino acids present in N-Myristoyltransferase are hydrophobic (46.1%). Secondary structure analysis shows predominance of alpha helices and random coils. Motif analyses revealed that this target protein contains 2 signature motifs, i.e., EVNFLCVHK and KFGEGDG. Apart from motif search, three-dimensional model was generated and validated and the stereo-chemical quality check confirmed that 97.7% amino acid residues fall in the core region of Ramachandran plot. Molecular dynamics simulation resulted in maximum 1.3 Å Root Mean Square Deviation (RMSD) between the initial structure and the trajectories obtained later on. The template and the target molecule has shown 1.5 Å RMSD for the C alpha trace. A docking study was also conducted with various ligand molecules among which specific benzofuran compounds turned out to be effective. This derived information will help in designing new inhibitor molecules for this target protein as well in better understanding the parasite protein.

• TOWARDS CLASSIFYING ORGANISMS BASED ON THEIR PROTEIN PHYSICOCHEMICAL PROPERTIES USING COMPARATIVE INTELLIGENT TECHNIQUES

  Amit Kumar Banerjee, Nayanoori Harikrishna, Jangam Vikram Kumar, Upadhyayula Suryanarayana Murty

  Applied Artificial Intelligence: An International Journal. 01/2011; 25:426-439.

  Several supervised and unsupervised methods are presently available for classification and clustering extremely nonlinear data sets. Biological data sets are known to be complex in nature due to their greater dimension, complex attribute interactions, and dynamic behavior. In this article, we presen... [more] Several supervised and unsupervised methods are presently available for classification and clustering extremely nonlinear data sets. Biological data sets are known to be complex in nature due to their greater dimension, complex attribute interactions, and dynamic behavior. In this article, we present the classification of 16 organisms based on physicochemical properties of their proteins employing comparative intelligent techniques. Considering the complexity of the present working data set, an attempt has been made to select the most important attributes using the feature selection facility available in TANAGRA (http://eric.univlyon2.fr/∼ricco/tanagra/en/tanagra.html) for better classification efficiency. Various methods available in LIB-SVM, a library for support vector machines, Waikato Environment for Knowledge Analysis (WEKA), and Konstanz Information Miner (KNIME) were utilized. Support vector machines (SVMs), radial basis function (RBF), polynomial, multiple layer perceptron (MLP), hyper-tangent, and sequential minimal optimization (SMO) were adopted to achieve maximum accuracy in the results. The best results obtained (>70%) are compared.

• Seaweeds: The Wealth of Oceans.Chapter 2

  Upadhyayula Suryanarayana Murty, Amit Kumar Banerjee

  Handbook of Marine Macroalgae: Biotechnology and Applied Phycology, First Edition. 01/2011; 1(1):(36-44) 567.

  Product Description from Amazon:(Courtesy:http://www.amazon.co.uk/Handbook-Marine-Macroalgae-Biotechnology-Phycology/dp/0470979186) The Handbook of Macroalgae: Biotechnology and Applied Phycology describes the biological, biotechnological and the industrial applications of seaweeds. Vast research in... [more] Product Description from Amazon:(Courtesy:http://www.amazon.co.uk/Handbook-Marine-Macroalgae-Biotechnology-Phycology/dp/0470979186) The Handbook of Macroalgae: Biotechnology and Applied Phycology describes the biological, biotechnological and the industrial applications of seaweeds. Vast research into the cultivation of seaweeds is currently being undertaken but there is a lack of methodological strategies in place to develop novel drugs from these sources. This book aims to rectify this situation, providing an important review of recent advances and potential new applications for macroalgae. Focusing on the chemical and structural nature of seaweeds the book brings the potentially valuable bioactive nature to the fore. Novel compounds isolated from seaweeds are reviewed to provide an invaluable reference for anyone working in the field.
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  Aspartate carbamoyltransferase of Plasmodium falciparum as a potential drug target for designing anti-malarial chemotherapeutic agents

  Amit Kumar Banerjee, Neelima Arora, Upadhyayula Surya Narayana Murty

  Medicinal Chemistry Research. 01/2011;

  Malaria remains one of the leading causes of deaths attributable to a communicable disease globally. The reemergence of drug-resistant Plasmodium falciparum, the most fatal human malarial parasite, has necessitated the exploration of different pathways to provide the urgently required novel drug tar... [more] Malaria remains one of the leading causes of deaths attributable to a communicable disease globally. The reemergence of drug-resistant Plasmodium falciparum, the most fatal human malarial parasite, has necessitated the exploration of different pathways to provide the urgently required novel drug targets. Aspartate carbamoyltransferase, an enzyme of de novo pyrimidine biosynthetic pathway in Plasmodium represents an attractive drug target. The enzyme was characterized using in silico tools. Tertiary (3D) structure of the enzyme was generated using the structure of Aspartate carbamoyltransferase of Pyrococcus abyssi (PDB ID: 1ML4) as template by comparative modeling and validated by various structural quality validation tools. The model was stable during the simulation with the equilibrium root-mean-square standard deviation value of ~1 Å. Results from structure assessment tools indicated the reasonably good quality of model. Several inhibitor molecules were docked in the active site of the modeled protein for determining the binding affinity of these molecules toward the protein. Out of various inhibitors used in the study, 3-(4-Hydroxy-phenyl)-2-(2-phosphono-acetylamino)-propionic acid showed highest binding affinity towards ACT. This study provides new insights towards understanding the 3-D Pf ACT structure and binding affinity of selected inhibitor compounds and also paves a way for designing novel anti-malarials.
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  Assessing the relationship among physicochemical properties of proteins with respect to hydrophobicity: a case study on AGC kinase superfamily.

  Amit Kumar Banerjee, B Poorna Manasa, Upadhyayula Suryanarayana Murty

  Indian journal of biochemistry & biophysics. 12/2010; 47(6):370-7.

  Understanding the protein structures is crucial, as it is involved in every cellular activity. Several experimental techniques, such as X-Ray crystallography, nuclear magnetic resonance and electron microscopy are available to gain insight about the structure and function of a protein molecule. Giga... [more] Understanding the protein structures is crucial, as it is involved in every cellular activity. Several experimental techniques, such as X-Ray crystallography, nuclear magnetic resonance and electron microscopy are available to gain insight about the structure and function of a protein molecule. Gigantic data on protein structural and sequential information is deposited in various repositories regularly which provide us the scope for more theoretical studies. Hydrophobicity always plays a vital role in tertiary structure formation and behavior of a protein molecule. This study focuses on elucidating influence of several physicochemical properties on hydrophobicity of AGC kinase proteins. AGC kinase superfamily is selected due to its tremendous structural and functional variability and sequence data availability. A combined data mining and stochastic approach confirmed that out of 47 parameters, transmembrane tendency influences the target variable most, followed by percent buried residues, GRAVY (Grand Average Hydropathicity) and aliphatic index. Calculating the influence of different physicochemical parameters and their interrelation will aid tremendously in the future of protein science.

• In silico characterization of Shikimate Kinase of Shigella flexneri: a potential drug target.

  Neelima Arora, Amit Kumar Banerjee, U S N Murty

  Interdisciplinary sciences, computational life sciences. 09/2010; 2(3):280-90.

  Shigella flexneri is a major pathogen responsible for Shigellosis causing massive morbidity among young population and imposes huge socio-economic burden. In this study, Shikimate Kinase (SK) from S. flexneri was characterized in silico and disordered regions were predicted. Motifs and domains were ... [more] Shigella flexneri is a major pathogen responsible for Shigellosis causing massive morbidity among young population and imposes huge socio-economic burden. In this study, Shikimate Kinase (SK) from S. flexneri was characterized in silico and disordered regions were predicted. Motifs and domains were calculated using computational tools. A three dimensional model of Shikimate Kinase of S.flexneri was constructed using Shikimate Kinase of E.coli (PDBID: 1KAG_A) as template by comparative modeling approach. Molecular dynamics calculations were carried out to check the stable conformation embedded in water sphere with least RMSD possible. Perusal of backbone conformation of the modeled structure by PROCHECK revealed that more than 98% of the residues fell in the allowed regions and ERRAT results confirmed good quality of modeled structure. Active site and its important residues were predicted for the derived model. Disulphide bridges were estimated by computational method and most probable pattern of cysteine residues was found in the pairs 8-22. Results of this study will shed light on the structural aspects of Shikimate Kinase of S. flexneri and will aid in rational drug designing.

• Bioinformatics with Solutions in Pest Management Science: An Insight into the Evolving Technologies

  U.S.N Murty, Amit Kumar Banerjee

  01/2010: pages 521-542;

  ISBN: 978-81-7800-227-9
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  Probing the structure of human glucose transporter 2 and analysis of protein ligand interactions

  Srikanth Duddela, P. Nataraj Sekhar, G. V. Padmavati, Amit Kumar Banerjee, U. S. N. Murty

  Medicinal Chemistry Research. 01/2010; 19:836-853.

  Diabetes is a metabolic disorder that has emerged recently as a major cause of global concern. Regulation of the blood glucose concentration is essential to maintain the homeostasis. GLUT2, a carrier protein, plays an important role in transporting sugar molecules across the membrane. To understand ... [more] Diabetes is a metabolic disorder that has emerged recently as a major cause of global concern. Regulation of the blood glucose concentration is essential to maintain the homeostasis. GLUT2, a carrier protein, plays an important role in transporting sugar molecules across the membrane. To understand the function of this carrier molecule, knowledge of its three-dimensional structure is of paramount importance. Homology modeling approach was adopted to decipher the three-dimensional structure and features of human GLUT2. Ninety-eight percent residues of the modeled structure lie in the allowed region of the Ramachandran plot and a RMSD of 0.86 Å with the template molecule confirms the reliability of the modeled structure. Comparative transmembrane helix prediction from primary sequence as well as analysis of model revealed presence of 12 helices, which is in agreement with the available literature. Molecular mechanical calculations and docking analysis were performed for the selected 33 compounds. Results showed Glipizide as the best interacting ligand based on the fitness values scored from the binding affinity and minimized energy of the docked complex. These results will aid in efficient designing of inhibitor molecules to curb diabetes.

• Homology model of 2C-methyl-d-erythritol 2, 4- cyclodiphosphate (MECP) synthase of Plasmodium falciparum 3D7

  Neelima Arora, Amit Kumar Banerjee, U.S.N Murty

  Electronic Journal of Biology. 01/2010; 6:52-57.

  Malaria has been a cause of enormous morbidity and mortality since the dawn of evolution. Control of malaria remains a farfetched dream despite numerous efforts and intervention strategies devised by research communities. Increasing drug resistance in the malarial parasite to conventional drugs has ... [more] Malaria has been a cause of enormous morbidity and mortality since the dawn of evolution. Control of malaria remains a farfetched dream despite numerous efforts and intervention strategies devised by research communities. Increasing drug resistance in the malarial parasite to conventional drugs has raised an alarm. This situation warrants the need for exploring novel drug targets. In this study, we report the structural modeling of an attractive drug target 2C-methyl-d-erythritol 2, 4- cyclodiphosphate (MECP) synthase. Threedimensional model of the enzyme was constructed using in-silico tools. The model was further evaluated for stereo-chemical quality. This model will provide an insight about the structure of MECP synthase and aid in rational drug design.

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• Target sites for microRNA expressed in pancreatic islets in Type 2 diabetes mellitus associated genes.

  Manika Pal-Bhadra, Neelima Arora, Shinde Santosh P, Paramita Ray, Amit Kumar Banerjee, Venkateswara Rao Sripathi, U.S.N Murty, Utpal Bhadra

  Online Journal of Bioinformatics. 01/2010; 11:245-263.

• Classification and clustering analysis of pyruvate dehydrogenase enzyme based on their physicochemical properties.

  Amit Kumar Banerjee, Sunita M, Naveen M, Upadhyayula Suryanarayana Murty

  Bioinformation. 01/2010; 4(10):456-62.

  Biological systems are highly organized and enormously coordinated maintaining greater complexity. The increment of secondary data generation and progress of modern mining techniques provided us an opportunity to discover hidden intra and inter relations among these non linear dataset. This will hel... [more] Biological systems are highly organized and enormously coordinated maintaining greater complexity. The increment of secondary data generation and progress of modern mining techniques provided us an opportunity to discover hidden intra and inter relations among these non linear dataset. This will help in understanding the complex biological phenomenon with greater efficiency. In this paper we report comparative classification of Pyruvate Dehydrogenase protein sequences from bacterial sources based on 28 different physicochemical parameters (such as bulkiness, hydrophobicity, total positively and negatively charged residues, α helices, β strand etc.) and 20 type amino acid compositions. Logistic, MLP (Multi Layer Perceptron), SMO (Sequential Minimal Optimization), RBFN (Radial Basis Function Network) and SL (simple logistic) methods were compared in this study. MLP was found to be the best method with maximum average accuracy of 88.20%. Same dataset was subjected for clustering using 2*2 grid of a two dimensional SOM (Self Organizing Maps). Clustering analysis revealed the proximity of the unannotated sequences with the Mycobacterium and Synechococcus genus.

• Structural model of the Plasmodium falciparum Thioredoxin reductase:a novel target for antimalarial drugs.

  Amit Kumar Banerjee, Neelima Arora, U S N Murty

  Journal of vector borne diseases. 10/2009; 46(3):171-83.

  Background: Malaria, a scourge of mankind, imposes a huge socioeconomic burden in tropical countries. Emergence of multi-drug resistant malarial parasites impels us to explore novel drug targets. Thioredoxin reductase is a promising antimalarial drug target. Methods: The Thioredoxin reductase enzyme... [more] Background: Malaria, a scourge of mankind, imposes a huge socioeconomic burden in tropical countries. Emergence of multi-drug resistant malarial parasites impels us to explore novel drug targets. Thioredoxin reductase is a promising antimalarial drug target. Methods: The Thioredoxin reductase enzyme of Plasmodium falciparum was characterized in silico and protein disorder was predicted using available online tools. Since the crystal structure of Thioredoxin reductase of P. falciparum is not yet available, its three-dimensional structure was constructed by homology modeling using the high-resolution Thioredoxin reductase type 2 of mouse as a template. Obtained model was further refined by Molecular Dynamics (MD). Results: The model was stable during the simulation with the equilibrium root mean square deviation (RMSD) value of 1.2 A. Stereochemical evaluation revealed that 99.1% residues of the constructed model lie in the most favoured and allowed regions, thus, indicating a good quality model. Conclusion: Results of this study will provide an insight into the structure of the Thioredoxin reductase of malarial parasite and aid in rational drug designing.

• Application of Kohonen maps for solving the classification puzzle in AGC kinase protein sequences.

  U S N Murty, Amit Kumar Banerjee, Neelima Arora

  Interdisciplinary sciences, computational life sciences. 09/2009; 1(3):173-8.

  Availability of enormous number of sequences in public domain databases warrants the need for effective tools for clustering and classification of such data. AGC protein kinase family is known to contain many enzymes involved in important cellular processes. In the present study, 21 important physic... [more] Availability of enormous number of sequences in public domain databases warrants the need for effective tools for clustering and classification of such data. AGC protein kinase family is known to contain many enzymes involved in important cellular processes. In the present study, 21 important physicochemical parameters were calculated for 115 sequences of AGC kinase family belonging to mouse and human. Kohonen maps, also known as Self Organizing Maps (SOM) were employed for the identification of clusters of similar sequences, projection and visualization of high dimensional data spaces owing to their capability of preserving topological relationships between the features. This simplistic approach can provide a method not only for studying intricate interplay of features and minute differences even in the members of same protein family but also for recognition of certain unifying common features. Each cluster obtained using SOM in this study has a distinct characteristic that sets it apart from the other clusters.

• An In Silico Approach to Cluster CAM Kinase Protein Sequences

  Murty U.S.N, Amit Kumar Banerjee, Arora Neelima

  Journal of Proteomics & Bioinformatics. 01/2009;

  As we are ushering in new age of data driven world, we face an enormous challenge of deriving information from heaps of data available. The amount of data being generated is overwhelming and this calls for exploring novel and effective methods for clustering and classification of such data. CAM kina... [more] As we are ushering in new age of data driven world, we face an enormous challenge of deriving information from heaps of data available. The amount of data being generated is overwhelming and this calls for exploring novel and effective methods for clustering and classification of such data. CAM kinase family is known to contain many enzymes involved in important physiological processes. In the present study, 13 important physicochemical parameters were calculated for 56 sequences of CAM kinase family in silico. Self organizing Maps (SOM) were employed for the classifying and clustering similar sequences and visualization of high dimensional data spaces as they are known for their capability to maintain the essence of topological relationships between the features. SOM effectively yielded 4 clusters which were distinct from each other and marked by characteristic features.

• Structural model of the Plasmodium falciparum Thioredoxin reductase:a novel target for antimalarial drugs

  Amit Kumar Banerjee, Arora Neelima, Murty U.S.N

  Journal of Vector Borne Diseases. 01/2009;

  Background: Malaria, a scourge of mankind, imposes a huge socioeconomic burden in tropicalcountries. Emergence of multi-drug resistant malarial parasites impels us to explore novel drugtargets. Thioredoxin reductase is a promising antimalarial drug target.Methods: The Thioredoxin reductase enzyme of... [more] Background: Malaria, a scourge of mankind, imposes a huge socioeconomic burden in tropicalcountries. Emergence of multi-drug resistant malarial parasites impels us to explore novel drugtargets. Thioredoxin reductase is a promising antimalarial drug target.Methods: The Thioredoxin reductase enzyme of Plasmodium falciparum was characterized insilico and protein disorder was predicted using available online tools. Since the crystal structure ofThioredoxin reductase of P. falciparum is not yet available, its three-dimensional structure wasconstructed by homology modeling using the high-resolution Thioredoxin reductase type 2 ofmouse as a template. Obtained model was further refined by Molecular Dynamics (MD).Results: The model was stable during the simulation with the equilibrium root mean square deviation(RMSD) value of 1.2 Å. Stereochemical evaluation revealed that 99.1% residues of the constructedmodel lie in the most favoured and allowed regions, thus, indicating a good quality model.Conclusion: Results of this study will provide an insight into the structure of the Thioredoxinreductase of malarial parasite and aid in rational drug designing.

• Clustering and Classification of Anopheline Spacer Sequences using Self Organizing Maps

  Amit Kumar Banerjee, Neelima Arora, U.S.N Murty

  The Internet Journal of Genomics and Proteomics. 01/2009; 4(1):1-22.

  ITS2, a well known phylogenetic marker is widely used in taxonomic studies. This study exploits a novel approach to classify and cluster the Anopheline species based upon their spacer (ITS2) sequences. As secondary structure of ITS2 is crucial for the function, derived parameters based on secondary ... [more] ITS2, a well known phylogenetic marker is widely used in taxonomic studies. This study exploits a novel approach to classify and cluster the Anopheline species based upon their spacer (ITS2) sequences. As secondary structure of ITS2 is crucial for the function, derived parameters based on secondary structure along with sequence composition were considered for this study. Self Organizing Map (SOM), a neural network approach was adopted for classification and clustering of Anopheline sequences. This data mining approach for clustering and classification will aid in unveiling of inherent relationships among the various parameters contributing to ITS2 structure stability.

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• Comparative characterization of commercially important xylanase enzymes.

  Neelima Arora, Amit Kumar Banerjee, Srilaxmi Mutyala, Upadhyayula Suryanarayana Murty

  Bioinformation. 01/2009; 3(10):446-53.

  Xylanase is an industrially important enzyme having wide range of applications especially in paper industry. It is crucial to gain an understanding about the structure and functional aspects of various xylanases produced from diverse sources. In this study, a bioinformatics and molecular modeling ap... [more] Xylanase is an industrially important enzyme having wide range of applications especially in paper industry. It is crucial to gain an understanding about the structure and functional aspects of various xylanases produced from diverse sources. In this study, a bioinformatics and molecular modeling approach was adopted to explore properties and structure of xylanases. Physico-chemical properties were predicted and prediction of motifs, disulfide bridges and secondary structure was performed for functional characterization. Apart from these analyses, three dimensional structures were constructed and stereo-chemical quality was evaluated by different structure validation tools. Comparative catalytic site analysis and assessment was performed to extract information about the important residues. Asn72 was found to be the common residue in the active sites of the proteins P35809 and Q12603.
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  Classification and identification of mosquito species using artificial neural networks.

  Amit Kumar Banerjee, K Kiran, U S N Murty, Ch Venkateswarlu

  Computational biology and chemistry. 08/2008;

  An artificial neural network method is presented for classification and identification of Anopheles mosquito species based on the internal transcribed spacer2 (ITS2) data of ribosomal DNA string. The method is implemented in two different multi-layered feed-forward neural network model forms, namely... [more] An artificial neural network method is presented for classification and identification of Anopheles mosquito species based on the internal transcribed spacer2 (ITS2) data of ribosomal DNA string. The method is implemented in two different multi-layered feed-forward neural network model forms, namely, multi-input single-output neural network (MISONN) and multi-input multi-output neural network (MIMONN). A number of data sequences in varying sizes of different Anopheline malarial vectors and their corresponding species coding are employed to develop the neural network models. The classification efficiency of the network models for untrained data sequences is evaluated in terms of quantitative performance criteria. The results demonstrate the efficiency of the neural network models to extract the genetic information in ITS2 sequences and to adapt to new data. The method of MISONN is found to exhibit superior performance over MIMONN in distinguishing and identification of the mosquito vectors.

• Exploring the Interplay of Sequence and Structural Features in Determiming the Flexibility of AGC Kinase Protein Family : A Bioinformatics Approach

  Amit Kumar Banerjee, Arora Neelima, Pranitha Varakantham, U.S.N.Murty

  Journal of Proteomics & Bioinformatics. 01/2008;

  In this study, data mining approach was used to generate association rules for predicting average flexibility from the various derived sequence and structural features. 21 parameters were calculated and their variable importance was calculated for 115 sequences of AGC kinase family belonging to mous... [more] In this study, data mining approach was used to generate association rules for predicting average flexibility from the various derived sequence and structural features. 21 parameters were calculated and their variable importance was calculated for 115 sequences of AGC kinase family belonging to mouse and human using Classification and Regression Tree (CART). Beta turns were found to have maximum influence on average flexibility while the total beta strands were found to exert minimum impact on average flexibility. Understanding the variable importance will prove useful as a simple pr edictor of flexibility from an amino acid sequence. This will aid in better understanding of phenomenon underlying the average flexibility and thus, will pave a way for rational design of therapeutics.

• Classification and Regression Tree (CART) Analysis for Deriving Variable Importance of Parameters Influencing Average Flexibility of CaMK Kinase Family

  Amit Kumar Banerjee, Neelima Arora, U.S.N Murty

  Electronic Journal of Biology. 01/2008; 4:27-33.

  In this study, data mining approach was used to derive decision rules for predicting average flexibility from the various derived sequence and structural features. 21 parameters were calculated and variable importance was calculated for 101 sequences of CaMK kinase family belonging to mouse and huma... [more] In this study, data mining approach was used to derive decision rules for predicting average flexibility from the various derived sequence and structural features. 21 parameters were calculated and variable importance was calculated for 101 sequences of CaMK kinase family belonging to mouse and human using Classification and Regression Tree (CART). Coils were found to have maximum influence on average flexibility while the Parallel beta strands were found to exert minimum impact on average flexibility. Understanding the variable importance will prove useful as a simple predictor of flexibility from an amino acid sequence. This will aid in better understanding of phenomenon underlying the average flexibility and thus, will pave a way for rational design of therapeutics and development of proper parametric weight distribution for existing molecular dynamics and protein folding algorithms.

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