Hifzur Rahman Ansari

Dr. Hifzur Rahman Ansari

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Research Focus & Metrics

Academic Career Length

18Years (2009-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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7 May 2013 in PLOS ONE
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Journal Article
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Harinder SinghHarinder Singh
Harinder Singh
HAHifzur Rahman Ansari
Hifzur Rahman Ansari
Gajendra P S RaghavaGajendra P S Raghava
Gajendra P S Raghava
One of the major challenges in designing a peptide-based vaccine is the identification of antigenic regions in an antigen that can stimulate B-cell’s response, also called B-cell epitopes. In the past, several methods have been developed for the prediction of conformational and linear (or continuous) B-cell epitopes. However, the existing methods for predicting linear B-cell epitopes are far from perfection. In this study, an attempt has been made to develop an improved method for predicting linear B-cell epitopes. We have retrieved experimentally validated B-cell epitopes as well as non B-cell epitopes from Immune Epitope Database and derived two types of datasets called Lbtope_Variable and Lbtope_Fixed length datasets. The Lbtope_Variable dataset contains 14876 B-cell epitope and 23321 non-epitopes of variable length where as Lbtope_Fixed length dataset contains 12063 B-cell epitopes and 20589 non-epitopes of fixed length. We also evaluated the performance of models on above datasets after removing highly identical peptides from the datasets. In addition, we have derived third dataset Lbtope_Confirm having 1042 epitopes and 1795 non-epitopes where each epitope or non-epitope has been experimentally validated in at least two studies. A number of models have been developed to discriminate epitopes and non-epitopes using different machine-learning techniques like Support Vector Machine, and K-Nearest Neighbor. We achieved accuracy from ∼54% to 86% using diverse s features like binary profile, dipeptide composition, AAP (amino acid pair) profile. In this study, for the first time experimentally validated non B-cell epitopes have been used for developing method for predicting linear B-cell epitopes. In previous studies, random peptides have been used as non B-cell epitopes. In order to provide service to scientific community, a web server LBtope has been developed for predicting and designing B-cell epitopes ( http://crdd.osdd.net/raghava/lbtope/ ).

1 January 2010 in Immunome Research
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Journal Article
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HAHifzur Rahman Ansari
Hifzur Rahman Ansari
Gajendra P S RaghavaGajendra P S Raghava
Gajendra P S Raghava
One of the major challenges in the field of vaccine design is to predict conformational B-cell epitopes in an antigen. In the past, several methods have been developed for predicting conformational B-cell epitopes in an antigen from its tertiary structure. This is the first attempt in this area to predict conformational B-cell epitope in an antigen from its amino acid sequence.

11 July 2014 in Genome Research
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Journal Article
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ARAdam J. Reid
Adam J. Reid
DBDamer Blake
Damer Blake
HAHifzur Rahman Ansari
Hifzur Rahman Ansari
KBKaren Billington
Karen Billington
HBHilary P. Browne
Hilary P. Browne
APArnab Pain
Arnab Pain
Global production of chickens has trebled in the past two decades and they are now the most important source of dietary animal protein worldwide. Chickens are subject to many infectious diseases that reduce their performance and productivity. Coccidiosis, caused by apicomplexan protozoa of the genus Eimeria, is one of the most important poultry diseases. Understanding the biology of Eimeria parasites underpins development of new drugs and vaccines needed to improve global food security. We have produced annotated genome sequences of all seven species of Eimeria that infect domestic chickens, which reveal the full extent of previously described repeat-rich and repeat-poor regions and show that these parasites possess the most repeat-rich proteomes ever described. Furthermore, while no other apicomplexan has been found to possess retrotransposons, Eimeria is home to a family of chromoviruses. Analysis of Eimeria genes involved in basic biology and host-parasite interaction highlights adaptations to a relatively simple developmental life cycle and a complex array of co-expressed surface proteins involved in host cell binding.

15 July 2015 in eLife
Verified
Journal Article
Open access
YWYong H Woo
Yong H Woo
HAHifzur Rahman Ansari
Hifzur Rahman Ansari
TOThomas D Otto
Thomas D Otto
CKChristen M Klinger
Christen M Klinger
MKMartin Kolisko
Martin Kolisko
APArnab Pain
Arnab Pain
The eukaryotic phylum Apicomplexa encompasses thousands of obligate intracellular parasites of humans and animals with immense socio-economic and health impacts. We sequenced nuclear genomes of Chromera velia and Vitrella brassicaformis, free-living non-parasitic photosynthetic algae closely related to apicomplexans. Proteins from key metabolic pathways and from the endomembrane trafficking systems associated with a free-living lifestyle have been progressively and non-randomly lost during adaptation to parasitism. The free-living ancestor contained a broad repertoire of genes many of which were repurposed for parasitic processes, such as extracellular proteins, components of a motility apparatus, and DNA- and RNA-binding protein families. Based on transcriptome analyses across 36 environmental conditions, Chromera orthologs of apicomplexan invasion-related motility genes were co-regulated with genes encoding the flagellar apparatus, supporting the functional contribution of flagella to the evolution of invasion machinery. This study provides insights into how obligate parasites with diverse life strategies arose from a once free-living phototrophic marine alga.

30 October 2013 in Biology Direct
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Journal Article
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SGSudheer Gupta
Sudheer Gupta
HAHifzur Rahman Ansari
Hifzur Rahman Ansari
AGAnkur Gautam
Ankur Gautam
OCOpen Source Drug Discovery Consortium
Open Source Drug Discovery Consortium
Gajendra P S RaghavaGajendra P S Raghava
Gajendra P S Raghava
Background: In the past, numerous methods have been developed for predicting antigenic regions or B-cell epitopes that can induce B-cell response. To the best of authors’ knowledge, no method has been developed for predicting B-cell epitopes that can induce a specific class of antibody (e.g.,IgA, IgG) except allergenic epitopes (IgE). In this study, an attempt has been made to understand the relation between primary sequence of epitopes and the class of antibodies generated.Results: The dataset used in this study has been derived from Immune Epitope Database and consists of 14725 B-cell epitopes that include 11981 IgG, 2341 IgE, 403 IgA specific epitopes and 22835 non-B-cell epitopes. In order to understand the preference of residues or motifs in these epitopes, we computed and compared amino acid and dipeptide composition of IgG, IgE, IgA inducing epitopes and non-B-cell epitopes. Differences in composition profiles of different classes of epitopes were observed, and few residues were found to be preferred. Based on these observations, we developed models for predicting antibody class-specific B-cell epitopes using various features like amino acid composition, dipeptide composition, and binary profiles. Among these, dipeptide composition-based support vector machine model achieved maximum Matthews correlation coefficient of 0.44, 0.70 and 0.45 for IgG, IgE and IgA specific epitopes respectively. All models were developed on experimentally validated non-redundant dataset and evaluated using five-fold cross validation. In addition, the performance of dipeptide-based model was also evaluated on independent dataset.Conclusion: Present study utilizes the amino acid sequence information for predicting the tendencies of antigens to induce different classes of antibodies. For the first time,in silicomodels have been developed for predicting B-cell epitopes, which can induce specific class of antibodies. A web service called IgPred has been developed to serve the scientific community. This server will be useful for researchers working in the field of subunit/epitope/peptide-based vaccines and immunotherapy (http://crdd.osdd.net/raghava/igpred/).Reviewers: This article was reviewed by Dr. M Michael Gromiha, Dr Christopher Langmead (nominated by Dr Robert Murphy) and Dr Lina Ma (nominated by Dr Zhang Zhang).

1 October 2016 in International Journal for Parasitology
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Journal Article
Open access
HAHifzur Rahman Ansari
Hifzur Rahman Ansari
TTThomas J. Templeton
Thomas J. Templeton
ASAmit Kumar Subudhi
Amit Kumar Subudhi
ARAbhinay Ramaprasad
Abhinay Ramaprasad
JTJianxia Tang
Jianxia Tang
APArnab Pain
Arnab Pain
Malaria in humans is caused by six species of Plasmodium parasites, of which the nuclear genome sequences for the two Plasmodium ovale spp., P. ovale curtisi and P. ovale wallikeri, and Plasmodium malariae have not yet been analyzed. Here we present an analysis of the nuclear genome sequences of these three parasites, and describe gene family expansions therein. Plasmodium ovale curtisi and P. ovale wallikeri are genetically distinct but morphologically indistinguishable and have sympatric ranges through the tropics of Africa, Asia and Oceania. Both P. ovale spp. show expansion of the surfin variant gene family, and an amplification of the Plasmodium interspersed repeat (pir) superfamily which results in an approximately 30% increase in genome size. For comparison, we have also analyzed the draft nuclear genome of P. malariae, a malaria parasite causing mild malaria symptoms with a quartan life cycle, long-term chronic infections, and wide geographic distribution. Plasmodium malariae shows only a moderate level of expansion of pir genes, and unique expansions of a highly diverged transmembrane protein family with over 550 members and the gamete P25/27 gene family. The observed diversity in the P. ovale wallikeri and P. ovale curtisi surface antigens, combined with their phylogenetic separation, supports consideration that the two parasites be given species status.