Novel point mutations in sulfadoxine resistance genes of Plasmodium falciparum from India

Garg, Shilpi; Saxena, Vishal; Kanchan, Swarna; Sharma, Pooja; Mahajan, Siddharth; Kochar, Dhanpat Kumar; Das, Ashis

doi:10.1016/j.actatropica.2009.01.009

Cited by 23 publications

(15 citation statements)

References 21 publications

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“…In addition, no mutation was detected at codon I164L (associated with highly pyrimethamine-resistance) in any of the examined isolates before (Zakeri et al, 2010) and after (Afsharpad et al, 2012; the present study) the changes in the treatment policy in Iran. This result was in line with the previous reports from neighboring countries, Afghanistan (Awab et al, 2013), Pakistan (Khatoon et al, 2009;Ghanchi et al, 2011;Khattak et al, 2013;Kolaczinski et al, 2012), and India (Ahmed et al, 2004;Garg et al, 2009). Furthermore, a significant decrease (P < 0.05) was observed in double mutations/wild types of pfdhfrpfdhps (R 59 N 108 /A 437 ) in the study areas from 2004 (83.5%) to 2010 (53.5%) (Zakeri et al, 2010;Afsharpad et al, 2012), and more reduction was detected among the samples collected during 2012-2014 (18%, the present study).…”

Section: Discussionsupporting

confidence: 95%

“…Nevertheless, with no clear reason, a sharp increase was observed in N 51 R 59 N 108 I 164 /S 436 G 437 haplotype from 2010 to 2014, which is the same as what was reported from Northeastern India (Mishra et al, 2014). The predominant pfdhfr haplotype in Iran seems to be N51,59R,108N rather than 51I,59R,108N similar to the previous reports from Afghanistan (Awab et al, 2013), Pakistan (Khatoon et al, 2009;Ghanchi et al, 2011;Kolaczinski et al, 2012), India (Biswas et al, 2000;Ahmed et al, 2004;Garg et al, 2009), Sri Lanka (Hapuarachchi et al, 2006), and Papua New Guinea (Mita et al, 2006). Therefore, mutation 51I might be a good molecular marker for rapid detection of triple mutant, showing pyrimethamine failure in Iran and its neighboring countries, Afghanistan and Pakistan.…”

Section: Discussionsupporting

confidence: 89%

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High prevalence of pfdhfr–pfdhps triple mutations associated with anti-malarial drugs resistance in Plasmodium falciparum isolates seven years after the adoption of sulfadoxine–pyrimethamine in combination with artesunate as first-line treatment in Iran

Rouhani

Zakeri

Pirahmadi

et al. 2015

Infection, Genetics and Evolution

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Section: Discussionsupporting

confidence: 95%

Section: Discussionsupporting

confidence: 89%

High prevalence of pfdhfr–pfdhps triple mutations associated with anti-malarial drugs resistance in Plasmodium falciparum isolates seven years after the adoption of sulfadoxine–pyrimethamine in combination with artesunate as first-line treatment in Iran

Rouhani

Zakeri

Pirahmadi

et al. 2015

Infection, Genetics and Evolution

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“…These combinations of mutations were not detected in the present study sites which are in nearby states. The dhfr double mutations (S108N + C59R) were the most prevalent here similar to other reported results [22]. This study did not detect any quadruple mutations in dhfr such as those reported from the Andaman and Nicobar Islands by Ahmed [20] and Das et al [23].…”

Section: Discussionsupporting

confidence: 91%

A clinical and molecular study of artesunate + sulphadoxine-pyrimethamine in three districts of central and eastern India

Srivastava

Ratha

Shah

et al. 2013

Malar J

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BackgroundArtesunate + sulphadoxine-pyrimethamine (AS + SP) is recommended throughout India as the first-line treatment for uncomplicated falciparum malaria. Due to the presence of several eco-epidemiological zones of malaria and variable drug pressure, it is necessary to evaluate the efficacy of this combination in different regions of India. The objective of this study was to use clinical and molecular methods to monitor the efficacy of AS + SP in three diverse sites.MethodsThe study was undertaken in three high endemic sites of central and eastern India. Patients with uncomplicated falciparum malaria were enrolled and followed for 28 days. Molecular genotyping was conducted for merozoite surface protein (msp1 and msp2) to differentiate between re-infection and recrudescence and for the dhfr and dhps genes to monitor antifolate drug resistance.ResultsIn all, 149 patients were enrolled at the three sites. The crude cure rates were 95.9%, 100%, and 100% in Ranchi, Keonjhar, and West Garo Hills respectively. PCR-corrected cure rates were 100% at all sites. In dhfr, 27% of isolates had triple mutations, while 46% isolates were double-mutants. The most prevalent mutation was S108N followed by C59R. 164 L mutation was observed in 43/126 (34%) isolates. In dhps, most (76%) of the isolates were wild-type. Only 2.5% (2/80) isolates showed double mutation. dhfr-dhps two locus mutation were observed in 16% (13/80) isolates. Parasite clearance time was not related with antifolate mutations.ConclusionsAS + SP combination therapy remained effective against falciparum malaria despite common mutations promoting resistance to antifolate drugs. Although the prevalence of double and triple mutations in dhfr was high, the prevalence of dhfr-dhps two locus mutations were low. Even isolates with dhfr triple and dhfr-dhps two locus mutations achieved adequate clinical and parasitological response.

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“…Comparative modeling may also be used to study the drug resistance in many vectors. Garg et al (2009) constructed the comparative model of dihydropteroate synthase protein which illustrated that novel point mutations at two positions may lead to sulphadoxine drug resistance in Plasmodium falciparum. Compararative models facilitates molecular replacement in X-ray structure/NMR models which allows refinement of a determined structure through the knowledge of already known structures.The computational prediction of protein structure also serves as an alternative to produce raw informations that may be validated by wet lab experiments.…”

Section: Caspmentioning

confidence: 99%

Secondary and Tertiary Structure Prediction of Proteins: A Bioinformatic Approach

Kesheri

Kanchan²,

Chowdhury³

et al. 2014

Complex System Modelling and Control Through Intelligent Soft Computations

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Correct prediction of secondary and tertiary structure of proteins is one of the major challenges in bioinformatics/computational biological research. Predicting the correct secondary structure is the key to predict a good/satisfactory tertiary structure of the protein which not only helps in prediction of protein function but also in prediction of sub-cellular localization. This chapter aims to explain the different algorithms and methodologies, which are used in secondary structure prediction. Similarly, tertiary structure prediction has also emerged as one of developing areas of bioinformatics/computational biological research owing to the large gap between the available number of protein sequences and the known experimentally solved structures. Because of time and cost intensive experimental methods, experimentally determined structures are not available for vast majority of the available protein sequences present in public domain databases. The primary aim of this chapter is to offer a detailed conceptual insight to the algorithms used for protein secondary and tertiary structure prediction. This chapter systematically illustrates flowchart for selecting the most accurate prediction algorithm among different categories for the target sequence against three categories of tertiary structure prediction methods. Out of the three methods, homology modeling which is considered as most reliable method is discussed in detail followed by strengths and limitations for each of these categories. This chapter also explains different practical and conceptual problems, obstructing the high accuracy of the protein structure in each of the steps for all the three methods of tertiary structure prediction. The popular hybrid methodologies which further club together a number of features such as structural alignments, solvent accessibility and secondary structure information are also discussed. Moreover, this chapter elucidates about the Meta-servers that generate consensus result from many servers to build a protein model of high accuracy. Lastly, scope for further research in order to bridge existing gaps and for developing better secondary and tertiary structure prediction algorithms is also highlighted.

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Novel point mutations in sulfadoxine resistance genes of Plasmodium falciparum from India

Cited by 23 publications

References 21 publications

High prevalence of pfdhfr–pfdhps triple mutations associated with anti-malarial drugs resistance in Plasmodium falciparum isolates seven years after the adoption of sulfadoxine–pyrimethamine in combination with artesunate as first-line treatment in Iran

High prevalence of pfdhfr–pfdhps triple mutations associated with anti-malarial drugs resistance in Plasmodium falciparum isolates seven years after the adoption of sulfadoxine–pyrimethamine in combination with artesunate as first-line treatment in Iran

A clinical and molecular study of artesunate + sulphadoxine-pyrimethamine in three districts of central and eastern India

Secondary and Tertiary Structure Prediction of Proteins: A Bioinformatic Approach

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