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1.  Construction and Analysis of the Cell Surface's Protein Network for Human Sperm-Egg Interaction 
ISRN bioinformatics  2013;2013:962760.
Sperm-egg interaction is one of the most impressive processes in sexual reproduction, and understanding the molecular mechanism is crucial in solving problems in infertility and failed in vitro fertilization. The main purpose of this study is to map the sperm-egg interaction network between cell-surface proteins and perform an interaction analysis on this new network. We built the first protein interaction network of human sperm-egg binding and fusion proteins that consists of 84 protein nodes and 112 interactions. The gene ontology analysis identified a number of functional clusters that may be involved in the sperm-egg interaction. These include G-protein coupled receptor protein signaling pathway, cellular membrane fusion, and single fertilization. The PPI network showed a highly interconnected network and identified a set of candidate proteins: ADAM-ZP3, ZP3-CLGN, IZUMO1-CD9, and ADAM2-IZUMO1 that may have an important role in sperm-egg interaction. The result showed that the ADAM2 may mediate interaction between two essential factors CD9 and IZUMO1. The KEGG analysis showed 12 statistically significant pathways with 10 proteins associated with cancer, suggesting a common pathway between tumor fusion and sperm-egg fusion. We believe that the availability of this map will assist future researches in the fertilization mechanism and will also facilitate biological interpretation of sperm-egg interaction.
PMCID: PMC4393059  PMID: 25937952
2.  CMD: A Database to Store the Bonding States of Cysteine Motifs with Secondary Structures 
Advances in Bioinformatics  2012;2012:849830.
Computational approaches to the disulphide bonding state and its connectivity pattern prediction are based on various descriptors. One descriptor is the amino acid sequence motifs flanking the cysteine residue motifs. Despite the existence of disulphide bonding information in many databases and applications, there is no complete reference and motif query available at the moment. Cysteine motif database (CMD) is the first online resource that stores all cysteine residues, their flanking motifs with their secondary structure, and propensity values assignment derived from the laboratory data. We extracted more than 3 million cysteine motifs from PDB and UniProt data, annotated with secondary structure assignment, propensity value assignment, and frequency of occurrence and coefficiency of their bonding status. Removal of redundancies generated 15875 unique flanking motifs that are always bonded and 41577 unique patterns that are always nonbonded. Queries are based on the protein ID, FASTA sequence, sequence motif, and secondary structure individually or in batch format using the provided APIs that allow remote users to query our database via third party software and/or high throughput screening/querying. The CMD offers extensive information about the bonded, free cysteine residues, and their motifs that allows in-depth characterization of the sequence motif composition.
PMCID: PMC3474208  PMID: 23091487
3.  A protein short motif search tool using amino acid sequence and their secondary structure assignment 
Bioinformation  2011;7(6):304-306.
We present the development of a web server, a protein short motif search tool that allows users to simultaneously search for a protein sequence motif and its secondary structure assignments. The web server is able to query very short motifs searches against PDB structural data from the RCSB Protein Databank, with the users defining the type of secondary structures of the amino acids in the sequence motif. The output utilises 3D visualisation ability that highlights the position of the motif in the structure and on the corresponding sequence. Researchers can easily observe the locations and conformation of multiple motifs among the results. Protein short motif search also has an application programming interface (API) for interfacing with other bioinformatics tools.
The database is available for free at
PMCID: PMC3280500  PMID: 22355226
Protein short motif search; protein secondary structure; visualization; application programming interface (API)
4.  Identification of putative drug targets for human sperm-egg interaction defect using protein network approach 
BMC Systems Biology  2015;9:37.
Sperm-egg interaction defect is a significant cause of in-vitro fertilization failure for infertile cases. Numerous molecular interactions in the form of protein-protein interactions mediate the sperm-egg membrane interaction process. Recent studies have demonstrated that in addition to experimental techniques, computational methods, namely protein interaction network approach, can address protein-protein interactions between human sperm and egg. Up to now, no drugs have been detected to treat sperm-egg interaction disorder, and the initial step in drug discovery research is finding out essential proteins or drug targets for a biological process. The main purpose of this study is to identify putative drug targets for human sperm-egg interaction deficiency and consider if the detected essential proteins are targets for any known drugs using protein-protein interaction network and ingenuity pathway analysis.
We have created human sperm-egg protein interaction networks with high confidence, including 106 nodes and 415 interactions. Through topological analysis of the network with calculation of some metrics, such as connectivity and betweenness centrality, we have identified 13 essential proteins as putative drug targets. The potential drug targets are from integrins, fibronectins, epidermal growth factor receptors, collagens and tetraspanins protein families. We evaluated these targets by ingenuity pathway analysis, and the known drugs for the targets have been detected, and the possible effective role of the drugs on sperm-egg interaction defect has been considered. These results showed that the drugs ocriplasmin (Jetrea©), gefitinib (Iressa©), erlotinib hydrochloride (Tarceva©), clingitide, cetuximab (Erbitux©) and panitumumab (Vectibix©) are possible candidates for efficacy testing for the treatment of sperm-egg interaction deficiency. Further experimental validation can be carried out to confirm these results.
We have identified the first potential list of drug targets for human sperm-egg interaction defect using the protein interaction network approach. The essential proteins or potential drug targets were found using topological analysis of the protein network. These putative targets are promising for further experimental validation. These study results, if validated, may develop drug discovery techniques for sperm-egg interaction defect and also improve assisted reproductive technologies to avoid in-vitro fertilization failure.
Electronic supplementary material
The online version of this article (doi:10.1186/s12918-015-0186-7) contains supplementary material, which is available to authorized users.
PMCID: PMC4506605  PMID: 26187737
Protein-protein interactions; Sperm-egg interaction; Essential proteins; Potential drug targets
5.  Interactions of non-natural halogenated substrates with D-specific dehalogenase (DehD) mutants using in silico studies 
The D-2-haloacid dehalogenase of D-specific dehalogenase (DehD) from Rhizobium sp. RC1 catalyses the hydrolytic dehalogenation of D-haloalkanoic acids, inverting the substrate-product configuration and thereby forming the corresponding L-hydroxyalkanoic acids. Our investigations were focused on DehD mutants: R134A and Y135A. We examined the possible interactions between these mutants with haloalkanoic acids and characterized the key catalytic residues in the wild-type dehalogenase, to design dehalogenase enzyme(s) with improved potential for dehalogenation of a wider range of substrates. Three natural substrates of wild-type DehD, specifically, monochloroacetate, monobromoacetate and D,L-2,3-dichloropropionate, and eight other non-natural haloalkanoic acids substrates of DehD, namely, L-2-chloropropionate; L-2-bromopropionate; 2,2-dichloropropionate; dichloroacetate; dibromoacetate; trichloroacetate; tribromoacetate; and 3-chloropropionate, were docked into the active site of the DehD mutants R134A and Y135A, which produced altered catalytic functions. The mutants interacted strongly with substrates that wild-type DehD does not interact with or degrade. The interaction was particularly enhanced with 3-chloropropionate, in addition to monobromoacetate, monochloroacetate and D,L-2,3-dichloropropionate. In summary, DehD variants R134A and Y135A demonstrated increased propensity for binding haloalkanoic acid and were non-stereospecific towards halogenated substrates. The improved characteristics in these mutants suggest that their functionality could be further exploited and harnessed in bioremediations and biotechnological applications.
PMCID: PMC4433833  PMID: 26019583
dehalogenases; docking; haloalkanoic acids; hydrogen-bond distance; interacting residues
7.  Counting in the dark: Non-intrusive laser scanning for population counting and identifying roosting bats 
Scientific Reports  2012;2:524.
Population surveys and species recognition for roosting bats are either based on capture, sight or optical-mechanical count methods. However, these methods are intrusive, are tedious and, at best, provide only statistical estimations. Here, we demonstrated the successful use of a terrestrial Light Detection and Ranging (LIDAR) laser scanner for remotely identifying and determining the exact population of roosting bats in caves. LIDAR accurately captured the 3D features of the roosting bats and their spatial distribution patterns in minimal light. The high-resolution model of the cave enabled an exact count of the visibly differentiated Hipposideros larvatus and their roosting pattern within the 3D topology of the cave. We anticipate that the development of LIDAR will open up new research possibilities by allowing researchers to study roosting behaviour within the topographical context of a cave's internal surface, thus facilitating rigorous quantitative characterisations of cave roosting behaviour.
PMCID: PMC3401962  PMID: 22826802
8.  Structure Prediction, Molecular Dynamics Simulation and Docking Studies of D-Specific Dehalogenase from Rhizobium sp. RC1 
Currently, there is no three-dimensional structure of D-specific dehalogenase (DehD) in the protein database. We modeled DehD using ab initio technique, performed molecular dynamics (MD) simulation and docking of D-2-chloropropionate (D-2CP), D-2-bromopropionate (D-2BP), monochloroacetate (MCA), monobromoacetate (MBA), 2,2-dichloropropionate (2,2-DCP), D,L-2,3-dichloropropionate (D,L-2,3-DCP), and 3-chloropropionate (3-CP) into the DehD active site. The sequences of DehD and D-2-haloacid dehalogenase (HadD) from Pseudomonas putida AJ1 have 15% sequence similarity. The model had 80% of the amino acid residues in the most favored region when compared to the crystal structure of DehI from Pseudomonas putida PP3. Docking analysis revealed that Arg107, Arg134 and Tyr135 interacted with D-2CP, and Glu20 activated the water molecule for hydrolytic dehalogenation. Single residue substitutions at 25–30 °C showed that polar residues of DehD were stable when substituted with nonpolar residues and showed a decrease in activity within the same temperature range. The molecular dynamics simulation of DehD and its variants showed that in R134A variant, Arg107 interacted with D-2CP, while in Y135A, Gln221 and Arg231 interacted with D-2CP. It is our emphatic belief that the new model will be useful for the rational design of DehDs with enhanced potentials.
PMCID: PMC3546658  PMID: 23443090
D-stereospecific dehalogenase; Rhizobium sp. RC1; DehD; interacting residues; docking; molecular dynamics simulation

Results 1-8 (8)