Sissades Tongsima

Pre-docking filter for protein and ligand 3D structures.

Virtual drug screening using protein-ligand docking techniques is a time-consuming process, which requires high computational power for binding affinity calculation. There are millions of chemical compounds available for docking. Eliminating compounds that are unlikely to exhibit high binding affinity from the screening set should speed-up the virtual drug screening procedure. We performed docking of 6353 ligands against twenty-one protein X-ray crystal structures. The docked ligands were ranked according to their calculated binding affinities, from which the top five hundred and the bottom five hundred were selected. We found that the volume and number of rotatable bonds of the top five hundred docked ligands are similar to those found in the crystal structures and corresponded with the volume of the binding sites. In contrast, the bottom five hundred set contains ligands that are either too large to enter the binding site, or too small to bind with high specificity and affinity to the binding site. A pre-docking filter that takes into account shapes and volumes of the binding sites as well as ligand volumes and flexibilities can filter out low binding affinity ligands from the screening sets. Thus, the virtual drug screening procedure speed is increased.

Characterising private and shared signatures of positive selection in 37 Asian populations

The Asian Diversity Project (ADP) assembled 37 cosmopolitan and ethnic minority populations in Asia that have been densely genotyped across over half a million markers to study patterns of genetic diversity and positive natural selection. We performed population structure analyses of the ADP populations and divided these populations into four major groups based on their genographic information. By applying a highly sensitive algorithm haploPS to locate genomic signatures of positive selection, 140 distinct genomic regions exhibiting evidence of positive selection in at least one population were identified. We examined the extent of signal sharing for regions that were selected in multiple populations and observed that populations clustered in a similar fashion to that of how the ancestry clades were phylogenetically defined. In particular, populations predominantly located in South Asia underwent considerably different adaptation as compared with populations from the other geographical regions. Signatures of positive selection present in multiple geographical regions were predicted to be older and have emerged prior to the separation of the populations in the different regions. In contrast, selection signals present in a single population group tended to be of lower frequencies and thus can be attributed to recent evolutionary events.

Bacterial communities on facial skin of teenage and elderly Thai females

The Human Microbiome Project was first established to understand the roles of human-associated microbes to human health and disease. This study presents preliminary findings of Thai female facial skin microbiome using three pooled samples from groups of skin microbiome profiles, namely (1) healthy and (2) acne-prone young adults (teenage.hea and teenage.acn) and (3) healthy elderly adults (elderly.hea) based on standard dermatological criteria. These samples were sequenced using 454-pyrosequencing targeting 16S rRNA (V3–V4 regions). Good’s coverage index of greater than 92% shows sufficient sampling of our data for each group. Three unique OTUs for each microbiome profile (43, 258 and 59 for teenage.hea, teenage.acn and ederly.hea, respectively) were obtained with 134 shared OTUs among the three datasets. Based on Morisita–Horn similarity coefficient, age is the major factor that brings the community relationship factor closer. The comparison among the three datasets reveal majority of Gemmatimonadetes, Planctomycetes and Nitrospirae in the teenage.hea, whereas Firmicutes are more prevalent in teenage.acn and elderly.hea skin types. In addition, when comparing Thai facial microbial diversity with the 16S data from U.S. forehead female database, significant differences were found among orders of bacteria, pointing to possible differences in human ecto-flora.

Molecular dynamics simulation of a human thiopurine S- methyltransferase complexed with 6-mercaptopurine model

Human thiopurine S-methyltransferase (TPMT) is an essential protein in 6-mercaptopurine (6MP) drug metabolism. To understand the pharmacogenetics of TPMT and 6MP, X-ray co-crystal structures of TPMT complexes with S-adenosyl-L-methionine (AdoMet) and 6MP are required. However, the co-crystal structure of this complex has not been reported because 6MP is poorly water soluble. We used molecular dynamics (MD) simulation to predict the structure of the complex of human TPMT-AdoHcy(CH2)6MP, where the sulfur atoms of AdoHcy and 6MP were linked by a CH2 group. After 1300 picoseconds of MD simulation, the trajectory showed that 6MP was stabilized in the TPMT active site by formation of non-bonded interactions between 6MP and Phe40, Pro196 and Arg226 side chains of TPMT. The intersulfur distance between AdoHcy and 6MP as well as the binding modes and the interactions of our TPMT-AdoHcy model are consistent with those observed in the X-ray crystal structure of murine TPMT-AdoHcy-6MP complex. The predicted binding modes of AdoHcy and 6MP in our model are consistent with those observed in murine TPMT X-ray crystal structures, which provides structural insights into the interactions of TPMT, AdoHcy, and 6MP at the atomic level and may be used as a starting point for further study of thiopurine drug pharmacogenetics.

Diversity of bacterial communities on the facial skin of different age-group Thai males

Background Skin microbiome varies from person to person due to a combination of various factors, including age, biogeography, sex, cosmetics and genetics. Many skin disorders appear to be related to the resident microflora, yet databases of facial skin microbiome of many biogeographies, including Thai, are limited. Methods Metagenomics derived B-RISA and 16S rRNA gene sequencing was utilized to identify the culture-independent bacterial diversity on Thai male faces (cheek and forehead areas). Skin samples were categorized (grouped) into (i) normal (teenage.hea) and (ii) acne-prone (teenage.acn) young adults, and normal (iii) middle-aged (middle.hea) and (iv) elderly (elderly.hea) adults. Results The 16S rRNA gene sequencing was successful as the sequencing depth had an estimated >98% genus coverage of the true community. The major diversity was found between the young and elderly adults in both cheek and forehead areas, followed by that between normal and acne young adults. Detection of representative characteristics indicated that bacteria from the order Rhizobiales, genera Sphingomonas and Pseudoalteromonas, distinguished the elderly.hea microbiota, along the clinical features of wrinkles and pores. Prediction of the metabolic potential revealed reduced metabolic pathways involved in replication and repair, nucleotide metabolism and genetic translation in the elderly.hea compared with that in the teenage.hea. For young adults, some unique compositions such as abundance of Propionibacterium acnes and Staphylococcus epidermidis, with a minor diversity between normal and acne skins, were detected. The metabolic potentials of the acne vs. normal young adults showed that teenage.acn was low in many cellular processes (e.g., cell motility and environmental adaptation), but high in carbohydrate metabolism, which could support acne growth. Moreover, comparison with the age-matched males from the US (Boulder, Colorado) to gain insight into the diversity across national biogeography, revealed differences in the distribution pattern of species, although common bacteria were present in both biogeographical samples. Furthermore, B-RISA served as a crosscheck result to the 16S rRNA gene sequencing (i.e., differences between teenage and elderly microbiota). Conclusions This study revealed and compared the microbial diversity on different aged Thai male faces, and included analyses for representing the bacterial flora, the clinical skin characteristics, and comparison with the US age-matched. The results represent the first skin microbiota of Thai males, and helps the design of a large-scale skin microbiome study of Thais. The findings of the diversity among ages, skin type and national biogeography supported the importance of these traits in the skin microbiome and in developing a safe and sustainable treatment for acne and aging skin diseases.

Microbial communities in the reef water at Kham Island, lower Gulf of Thailand

Coral reefs are among the most biodiverse habitats on Earth, but knowledge of their associated marinemicrobiome remains limited. To increase the understanding of the coral reef ecosystem in the lower Gulf of Thailand, this study utilized 16S and 18S rRNA gene-based pyrosequencing to identify the prokaryotic and eukaryotic microbiota present in the reef water at Kham Island, Trat province, Thailand (N6.97 E100.86). The obtained result was then compared with the published microbiota from different coral reef water and marine sites. The coral reefs at Kham Island are of the fringe type. The reefs remain preserved and abundant. The community similarity indices (i.e., Lennon similarity index, Yue & Clayton similarity index) indicated that the prokaryotic composition of Kham was closely related to that of Kra, another fringing reef site in the lower Gulf of Thailand, followed by coral reef water microbiota at GS048b (Cooks Bay, Fr. Polynesia), Palmyra (Northern Line Islands, United States) and GS108b (Coccos Keeling, Australia), respectively. Additionally, the microbial eukaryotic populations at Kham was analyzed and compared with the available database at Kra. Both eukaryotic microbiota, in summer and winter seasons, were correlated. An abundance of Dinophysis acuminata was noted in the summer season, in accordance with its reported cause of diarrhoeatic shellfish outbreak in the summer season elsewhere. The slightly lower biodiversity in Kham than at Kra might reflect the partly habitat difference due to coastal anthropogenic activities and minor water circulation, as Kham locates close to the mainland and is surrounded by islands (e.g., Chang and Kut islands). The global marine microbiota comparison suggested relatively similar microbial structures among coral sites irrespective of geographical location, supporting the importance of coral-associated marine microbiomes, and Spearman’s correlation analysis between community membership and factors of shore distance and seawater temperature indicated potential correlation of these factors (p-values < 0.05) with Kham, Kra, and some other coral and coastal sites. Together, this study provided the second marine microbial database for the coral reef of the lower Gulf of Thailand, and a comparison of the coral-associated marine microbial diversity among global ocean sites.

ToNER: A tool for identifying nucleotide enrichment signals in feature-enriched RNA-seq data

Background Biochemical methods are available for enriching 5′ ends of RNAs in prokaryotes, which are employed in the differential RNA-seq (dRNA-seq) and the more recent Cappable-seq protocols. Computational methods are needed to locate RNA 5′ ends from these data by statistical analysis of the enrichment. Although statistical-based analysis methods have been developed for dRNA-seq, they may not be suitable for Cappable-seq data. The more efficient enrichment method employed in Cappable-seq compared with dRNA-seq could affect data distribution and thus algorithm performance. Results We present Transformation of Nucleotide Enrichment Ratios (ToNER), a tool for statistical modeling of enrichment from RNA-seq data obtained from enriched and unenriched libraries. The tool calculates nucleotide enrichment scores and determines the global transformation for fitting to the normal distribution using the Box-Cox procedure. From the transformed distribution, sites of significant enrichment are identified. To increase power of detection, meta-analysis across experimental replicates is offered. We tested the tool on Cappable-seq and dRNA-seq data for identifying Escherichia coli transcript 5′ ends and compared the results with those from the TSSAR tool, which is designed for analyzing dRNA-seq data. When combining results across Cappable-seq replicates, ToNER detects more known transcript 5′ ends than TSSAR. In general, the transcript 5′ ends detected by ToNER but not TSSAR occur in regions which cannot be locally modeled by TSSAR. Conclusion ToNER uses a simple yet robust statistical modeling approach, which can be used for detecting RNA 5′ends from Cappable-seq data, in particular when combining information from experimental replicates. The ToNER tool could potentially be applied for analyzing other RNA-seq datasets in which enrichment for other structural features of RNA is employed. The program is freely available for download at ToNER webpage (http://www4a.biotec.or.th/GI/tools/toner) and GitHub repository (https://github.com/PavitaKae/ToNER).

Fast processing of microscopic images using object-based extended depth of field

BackgroundMicroscopic analysis requires that foreground objects of interest, e.g. cells, are in focus. In a typical microscopic specimen, the foreground objects may lie on different depths of field necessitating capture of multiple images taken at different focal planes. The extended depth of field (EDoF) technique is a computational method for merging images from different depths of field into a composite image with all foreground objects in focus. Composite images generated by EDoF can be applied in automated image processing and pattern recognition systems. However, current algorithms for EDoF are computationally intensive and impractical, especially for applications such as medical diagnosis where rapid sample turnaround is important. Since foreground objects typically constitute a minor part of an image, the EDoF technique could be made to work much faster if only foreground regions are processed to make the composite image. We propose a novel algorithm called object-based extended depths of field (OEDoF) to address this issue.MethodsThe OEDoF algorithm consists of four major modules: 1) color conversion, 2) object region identification, 3) good contrast pixel identification and 4) detail merging. First, the algorithm employs color conversion to enhance contrast followed by identification of foreground pixels. A composite image is constructed using only these foreground pixels, which dramatically reduces the computational time.ResultsWe used 250 images obtained from 45 specimens of confirmed malaria infections to test our proposed algorithm. The resulting composite images with all in-focus objects were produced using the proposed OEDoF algorithm. We measured the performance of OEDoF in terms of image clarity (quality) and processing time. The features of interest selected by the OEDoF algorithm are comparable in quality with equivalent regions in images processed by the state-of-the-art complex wavelet EDoF algorithm; however, OEDoF required four times less processing time.ConclusionsThis work presents a modification of the extended depth of field approach for efficiently enhancing microscopic images. This selective object processing scheme used in OEDoF can significantly reduce the overall processing time while maintaining the clarity of important image features. The empirical results from parasite-infected red cell images revealed that our proposed method efficiently and effectively produced in-focus composite images. With the speed improvement of OEDoF, this proposed algorithm is suitable for processing large numbers of microscope images, e.g., as required for medical diagnosis.

Speedup bioinformatics applications on multicore-based processor using vectorizing and multithreading strategies.

Many computational intensive bioinformatics software, such as multiple sequence alignment, population structure analysis, etc., written in C/C++ are not multicore-aware. A multicore processor is an emerging CPU technology that combines two or more independent processors into a single package. The Single Instruction Multiple Data-stream (SIMD) paradigm is heavily utilized in this class of processors. Nevertheless, most popular compilers including Microsoft Visual C/C++ 6.0, x86 gnu C-compiler gcc do not automatically create SIMD code which can fully utilize the advancement of these processors. To harness the power of the new multicore architecture certain compiler techniques must be considered. This paper presents a generic compiling strategy to assist the compiler in improving the performance of bioinformatics applications written in C/C++. The proposed framework contains 2 main steps: multithreading and vectorizing strategies. After following the strategies, the application can achieve higher speedup by taking the advantage of multicore architecture technology. Due to the extremely fast interconnection networking among multiple cores, it is suggested that the proposed optimization could be more appropriate than making use of parallelization on a small cluster computer which has larger network latency and lower bandwidth.

Analysis of snake venom metalloproteinases from Myanmar Russell's viper transcriptome

&NA; Snake venom metalloproteinases (SVMPs) are the key enzymes in Russells viper (RV) venom which target all important components of haemostasis, such as clotting factors, platelets, endothelial cells and basement membrane. The structural diversity of SVMPs contributes to the broad spectrum of biological activities. The aim of the study was to investigate the SVMP transcript profile to gain better insights into the characteristic clinical manifestations of the Myanmar Russells viper (MRV) bites that distinguish it from the RVs of other habitats. Next generation sequencing (RNA‐Seq) of mRNA from MRV venom glands (2 males and 1 female) was performed on an Illumina HiSeq2000 platform and then de novo assembled using Trinity software. A total of 59 SVMP contigs were annotated through a Blastn search against the serpent nucleotide database from NCBI. Among them, disintegrins were the most abundant transcripts (75%) followed by the P‐III class SVMPs (25%). The P‐II SVMPs were scarce (0.002%), while no P‐I SVMPs were detectable in the transcriptome. For detailed structural analysis, contigs were conceptually translated and compared with amino acid sequences from other RVs and other vipers using Clustal Omega. The RTS‐disintegrin (jerdostatin homolog) was the most abundant among transcripts corresponding to 5 disintegrin isoforms. From 10 isoforms of SVMPs, RVV‐X, and Vipera lebetina apoptosis‐inducing protease (VLAIP) homolog, hereby termed Daboia siamensis AIP (DSAIP), were found to be highly expressed. Venom protein analysis using SDS‐PAGE followed by mass spectrometry revealed that the disintegrin was scarce, while the latter two SVMPs were abundant. These two proteins can contribute to severe clinical manifestations caused by MRV envenomation. HighlightsThe most abundant toxin transcripts in the Myanmar Russells viper transcriptome were annotated as metalloproteinases.Disintegrin transcripts were the most abundant transcripts (75%) followed by P‐III SVMPs (25%).Five isoforms of disintegrins and 10 isoforms of SVMPs were identified in the current transcriptomes.Protein analysis revealed that the disintegrin was scarce, while the P‐III SVMPs were abundant.The highly‐expressed P‐III SVMPs were RVV‐X and the novel Vipera lebetina apoptosis‐inducing protease (VLAIP) homolog.