Dimensional Structure Of Protein Research Articles

Nanoparticles insert a three dimensional cavity structure of proteins for function inhibition: The Case of CeO2 and SARS-CoV-2

The selective interaction of nanomaterials with proteins for protein function suppression has been reported. However, whether the nanomaterials could be used to target a three-dimensional (3D) structure of proteins for the consequent function inhibition is not defined. When SARS-CoV-2 binds to the host cell surface ACE2 receptor, the spike protein trimer changes to an "Open State" which forms a 5 nm cavity structure, consequently exposing the receptor binding domain (RBD) for the following viral infection. We found that the 3 nm cerium oxide nanoparticles (CeO2@3) showed a better anti-SARS-CoV-2 effect than 30 nm cerium oxide nanoparticles (CeO2@30). We performed a series of experiments and demonstrated that the CeO2@3 could target the 5 nm spike protein trimer cavity and tightly bind with the RBD, thus effectively blocking the following virus-cell interaction and rendering CeO2@3 as an effective anti-viral agent. As all coronaviruses possess similar spike protein structures as homologous proteins, CeO2@3 can be used as a broad-sperm anti-coronavirus nanodrug candidate by targeting the spike protein 3D structure. This work, for the first time, demonstrated that rationally engineered inorganic nanomaterials can be used to specifically target a 3D structure of a certain protein for function inhibition, thus providing a novel methodological approach and paving the way for future molecular targeting nanodrug candidate design.

Genome-wide identification and expression profiling of the BcSNAT family genes and their response to hormones and abiotic stresses in flowering Chinese cabbage

Flowering Chinese cabbage (Brassica rapa ssp. Chinensis var. parachinensis) is an economically important vegetable crop that is widely cultivated in southern China and worldwide. However, plants are sensitive to environmental cues that can significantly reduce crop production. Melatonin is a pineal gland hormone that acts as a plant signalling molecule in abiotic stress tolerance. Serotonin N-acetyltransferase (SNAT) family proteins play a central role in the melatonin biosynthesis pathway and in plant responses to environmental influences. Therefore, this study aimed to identify the SNAT family genes and characterise their functions in flowering Chinese cabbage. To assess the involvement of BcSNAT family genes in abiotic stress, we performed genome-wide characterisation of the BcSNAT family, including the identification of BcSNAT genes, phylogenetic relationships, chromosomal locations, two dimensional (D), and 3D protein structures, subcellular localisation, motif analysis, cis-regulatory elements, expression profiling in different tissues, hormone treatments, and abiotic stress responses. In the flowering Chinese cabbage genome, two SNAT genes were identified (BcSNAT1 and BcSNAT2) and named according to their chromosomal locations. Phylogenetic analysis revealed that the BcSNAT genes were divided into two groups (I and II) and exhibited high homology with other plant species. Numerous cis-elements, including hormone-, stress-, metabolism-, and development-responsive cis-elements, were identified in the promoter analysis of BcSNAT genes. BcSNAT genes were expressed in different tissues of flowering Chinese cabbage and responded to melatonin, hormone treatments, and abiotic stresses. It is anticipated that BcSNAT genes may play an important role in abiotic stress tolerance by activating the melatonin signalling pathway. The results of this study may provide a theoretical foundation for further research on genetic modifications to enhance the production of protected vegetables.

Recent Progress in Biosensors for Diagnosis of Cancer Cells, Tissues and Tumors Biomarkers

Raman spectroscopy is an important method for identifying molecules, which is widely used in determining the chemical and structural characteristics of various substances. Many materials have a special Raman spectrum, so that this phenomenon has turned the Raman device into an efficient tool for studying the structural and chemical properties of molecules. Since it is possible to obtain detailed information about the chemical and structural characteristics of biological compounds from Raman spectroscopy, the use of this method is rapidly expanding in the field of life sciences, especially in biological and medical studies. There is no need for special, time-consuming and expensive preparations in the study of materials with the help of a Raman device. In the protein Raman spectrum, distinct bands arise from the vibrational states of the peptide backbone and amino acid side chains. Therefore, based on the position and intensity of the protein’s Raman spectrum, it is possible to obtain valuable information about its second, third, and fourth structures. Also, the Raman spectrum of the protein contains information about the orientation and surrounding environment of the amino acid side chains. The correct formation of the disulfide bond in the protein structure can also be studied with the help of the Raman device. In general, the Raman spectrum of proteins contains multiple discrete bands that represent the vibrational states of the molecule and is used as a selective fingerprint to accurately determine the three–dimensional structure of proteins, intramolecular dynamics, and intermolecular interactions (Graphical Abstract).

Leading–Edge Portable Biosensors and Biomarkers Development for Raman Biospectroscopy and Imaging in Cancer Diagnosis

Raman spectroscopy is an important method for identifying molecules, which is widely used in determining the chemical and structural characteristics of various substances. Many materials have a special Raman spectrum, so that this phenomenon has turned the Raman device into an efficient tool for studying the structural and chemical properties of molecules. Since it is possible to obtain detailed information about the chemical and structural characteristics of biological compounds from Raman spectroscopy, the use of this method is rapidly expanding in the field of life sciences, especially in biological and medical studies. There is no need for special, time–consuming and expensive preparations in the study of materials with the help of a Raman device. In the protein Raman spectrum, distinct bands arise from the vibrational states of the peptide backbone and amino acid side chains. Therefore, based on the position and intensity of the protein's Raman spectrum, it is possible to obtain valuable information about its second, third, and fourth structures. Also, the Raman spectrum of the protein contains information about the orientation and surrounding environment of the amino acid side chains. The correct formation of the disulfide bond in the protein structure can also be studied with the help of the Raman device. In general, the Raman spectrum of proteins contains multiple discrete bands that represent the vibrational states of the molecule and is used as a selective fingerprint to accurately determine the three–dimensional structure of proteins, intramolecular dynamics, and intermolecular interactions.

Laser ablation combined with Nanoimprint Lithography technology as new surface engineering approach to produce novel polymer-based heteronucleants for recalcitrant protein crystallization

Macromolecule crystallography is currently the most powerful technique for determining the three dimensional structure of proteins at atomic resolution. However, despite its enormous level of technical development achieved, it is still limited by the great difficulty of obtaining crystals that, after exposure to X-rays, allow a high-resolution diffraction pattern from which the structure of the target protein can be elucidated. Even today, the crystallization process is a trial-and-error procedure that requires enormous experimental effort and high economic costs. In this research work, Laser Ablation technology in combination with NanoImprint Lithography was applied on Polycarbonate surfaces to produce novel heteronucleating agents containing multiscale surface topographies (in the micro- and submicro-scale) that promote the growth of protein crystals. Two human proteins, known to be recalcitrant to crystallization when using standard protocols, were used in the assays: (i) a construct of the CNNM4 magnesium transporter lacking amino acid residues 545–730 (HsCNNM4545-730) and (ii) cystathionine beta-synthase enzyme lacking residues 516–525 (HsCBSΔ516-525). The surface engineering solution was validated by comparing the number of novel crystallization conditions induced by those surfaces compared against the control and the use of the Naomi’s Nucleant, a commercially available heteronucleant made of mesoporous bioglass. The aspect ratio of the topography emerges as the topographical parameter that most contributes to protein growth on patterned surfaces. Additionally, the presence of a random distribution of micropores as well as a hierarchical (merging micro- and nano - scale features) surface topography also resulted in a more efficient crystallization process, showing an increment of between 38 and 68% in the number of new crystallization conditions, depending on the surface topography and protein selected. A conclusion is made that Laser Ablation with ultrashort pulses and the combination with Nanoimprint Lithography can be efficiently applied on polymeric substrates to produce a novel concept of heteronucleants that would bridge the gap to the development of universal nucleation agents.

Determination of Insecticidal Potential of Lentil (Lens culinaris L.) Lectin through Bio-computational Tools

Plant and animals are the chief source of lectins playing important role in defense system against various pathogens. Lentil (Lens culinaris) lectin (LL) binds to polysaccharides and other glycoconjugates in a reversibly manner which contain glucose or mannose type sugars. In present investigation, the insecticidal potential of LL is determined through In-silico study by using various bio-computational tools against mustard aphid. The physico-chemical property of LL also exhibited theoretical pI is 5.22, GRAVY value is -0.086, aliphatic index is 78.33 and instability index is 27.51. The functional domain exposure of LL showed metal interacting and N-linked glycosylated amino acid residues. The structural behavior and biological activity of LL protein is determined by secondary structure prediction and its other attributes. Present investigation explores the potential of insecticidal activity of lentil lectin against mustard aphid by using numerous In silico approaches. This probably helps in understanding of LL three dimensional protein structures.

In Silico Study of Secondary Structure of Hemoglobin Protein

Protein structure prediction is one of the important goals in the area of bioinformatics and biotechnology. Prediction methods include structure prediction of both secondary and tertiary structures of protein. Protein secondary structure prediction infers knowledge related to presence of helixes, sheets and coils in a polypeptide chain whereas protein tertiary structure prediction infers knowledge related to three dimensional structures of proteins. Protein secondary structures represent the possible motifs or regular expressions represented as patterns that are predicted from primary protein sequence in the form of alpha helix, betastr and and coils. The secondary structure prediction is useful as it infers information related to the structure and function of unknown protein sequence. There are various secondary structure prediction methods used to predict about helixes, sheets and coils. Based on these methods there are various prediction tools under study. This study includes prediction of hemoglobin using various tools. The results produced inferred knowledge with reference to percentage of amino acids participating to produce helices, sheets and coils. PHD and DSC produced the best of the results out of all the tools used.

Identification of novel polymorphism and in silico analysis of caprine DNAJB3 gene

• DNAJB3, a molecular chaperon, was analysed first time both in vivo and in silico in goat. • In the amplified complete coding sequence of caprine DNAJB3, one nucleotide substitution at 419 th (C > A) position was identified. • In silico structural analysis predicted change in amino acid (Ala > Glu) at 140 th position with minor difference (7%) in three dimensional protein structure. • Computational analysis showed differential interaction of the wild and mutant type DNAJB3 proteins with other stress related proteins. DNAJB3 acts as a cochaperon and stimulates ATPase activity of HSP family genes through its J domain. An in vivo and in silico study was conducted to get comprehensive idea on the role of DNAJB3 gene in goat. The coding sequence of DNAJB3 gene was amplified and searched for polymorphism in three indigenous goat (i.e. Black Bengal, Ganjam and Raighar) populations. One nucleotide substitution at 419th (C > A) position (wild and mutant) with resultant change in amino acid (Ala > Glu) at 140th position was identified. The comparative nucleotide sequence analysis showed 68 variable sites that included 53 parismony informative sites and 15 singleton sites. In silico structural analysis revealed minor difference (7%) in three dimensional protein structure between mutant and wild type DNAJB3 proteins. The protein-protein interactions of DNAJB3 with HSP72, JNK stress kinase, and IKKβ stress kinase were also predicted. The mutant (Raighar) type DNAJB3 protein predicted to interact only with A chain of the JNK stress kinase. Both the wild and mutant type variants of DNAJB3 proteins predicted to interact with A and B chain of hexamer IKKβ stress kinase. This study will be helpful to use DNAJB3 as a molecular marker for thermal tolerance in future.

Computational identification of potential lead molecules targeting rho receptor of Neisseria gonorrhoeae

Gonorrhea, one of the sexually transmitted disease caused by a gram negative diplococcus bacteria Neisseria gonorrhoeae. Rho protein is indispensable for bacterial viability due to its versatile functions in physiology apart from RNA dependent transcription termination. Based on conserved function and wider role in several cellular processes, inhibitors specifically targeting Rho proteins are largely in use these days to treat various bacterial infections. In this study, three dimensional structure of Rho protein was modeled using the template protein from E. coli and further the optimized model was simulated for 100 ns to understand the structural stability and compactness. Owing to the therapeutic potential of Rho, traditional structure-based virtual screening was applied to identify potential inhibitors for the selected target. Based on empirical glide scoring functions two potent lead molecules (ChemBridge_6121956 and ChemBridge_5232688) were selected from ChemBridge database. The pharmacokinetic properties of these lead molecules are within the permissible range. DFT descriptor revealed that the lead molecules are more reactive, which also supports the molecular docking studies. The stability of Rho and Rho-inhibitor complexes was studied using molecular dynamics simulation. Parameters include binding free energy calculation, RMSD, RMSF and hydrogen bond analysis depicts the stability of Rho and Rho-inhibitors throughout the simulation. Altogether, the identified lead molecules require further optimization towards the design and development of new antibiotics against N. gonorrhoeae. Communicated by Ramaswamy H. Sarma

Machine Learning Approaches on High Throughput NGS Data to Unveil Mechanisms of Function in Biology and Disease.

In this review, the fundamental basis of machine learning (ML) and data mining (DM) are summarized together with the techniques for distilling knowledge from state-of-the-art omics experiments. This includes an introduction to the basic mathematical principles of unsupervised/supervised learning methods, dimensionality reduction techniques, deep neural networks architectures and the applications of these in bioinformatics. Several case studies under evaluation mainly involve next generation sequencing (NGS) experiments, like deciphering gene expression from total and single cell (scRNA-seq) analysis; for the latter, a description of all recent artificial intelligence (AI) methods for the investigation of cell sub-types, biomarkers and imputation techniques are described. Other areas of interest where various ML schemes have been investigated are for providing information regarding transcription factors (TF) binding sites, chromatin organization patterns and RNA binding proteins (RBPs), while analyses on RNA sequence and structure as well as 3D dimensional protein structure predictions with the use of ML are described. Furthermore, we summarize the recent methods of using ML in clinical oncology, when taking into consideration the current omics data with pharmacogenomics to determine personalized treatments. With this review we wish to provide the scientific community with a thorough investigation of main novel ML applications which take into consideration the latest achievements in genomics, thus, unraveling the fundamental mechanisms of biology towards the understanding and cure of diseases.

Computational insight into the three-dimensional structure of ADP ribosylation factor like protein 15, a novel susceptibility gene for rheumatoid arthritis

The ARL15 gene (ADP ribosylation factor like protein 15) encodes for an uncharacterized small GTP-binding protein. Its exact role in human physiology remains unknown, but a number of genetic association studies have recognised different variants in this gene to be statistically associated with numerous traits and complex diseases. We have previously reported a novel association of ARL15 with rheumatoid arthritis (RA) based on a genome-wide association study in a north Indian cohort. Subsequent investigations have provided leads for its involvement in RA pathophysiology, especially its potential as a novel therapeutic target. However, the absence of an experimentally determined tertiary structure for ARL15 significantly hinders the understanding of its biochemical and physiological functions, as well as development of potential lead molecules. We, therefore, aimed to derive a high quality, refined model of the three dimensional structure of human ARL15 protein using two different computational protein structure prediction methods – template-based threading and ab initio modelling. The best model each from among the five each derived from both the approaches was selected based on stringent quality assessment and refinement. Molecular dynamics simulations over long timescales revealed the ab initio model to be relatively more stable, and it marginally outperformed the template-based model in the quality assessment as well. A putative GTP-binding site was also predicted using homology for the ARL15 protein, where potential competitive inhibitors can be targeted. This high quality predicted model may provide insights to the biological role(s) of ARL15 and inform and guide further experimental, structural and biochemical characterization efforts. Communicated by Ramaswamy H. Sarma

An integrative bioinformatics analysis of caprine GNAI3 gene

Goat is the most preferred domesticated animal in Indian subcontinent. However, the climatic change-induced heat stresscauses a formidable challenge for maintaining optimum productivity. G protein subunit alpha i3 (GNAI3) is one of the genes that may have significant role in heat tolerance mechanism in goats. The caprine GNAI3 gene was searched for homology analysis and its three dimensional protein structure was predicted followed by its validation through in silico approach. Nucleotide sequence-based phylogenetic tree analysis showed that the caprine GNAI3 gene has close evolutionary relationship with that of Ovis aries. Homology modelling of caprine GNAI3 protein was done in MODELLER 9.18 (P1), PHYRE2 (P2), GENO3D (P3) and SWISS MODEL (P4). The modelled structures were further validated after observing the Ramachandran and hydrophobicity plots. In the best of three dimensional protein structure (P4 as produced by SWISS MODEL), 330 (98.8%), three (0.9%) and one (0.3%) amino acid residues were found in favoured region, allowed region and outlier region, respectively. Degree of hydrophobicity of the generated protein structures revealed the presence of alternate hydrophobic and hydrophilic regions. The ligand receptor interaction site of the predicted 3D model was traced out using Discovery Studio 3.5. STRING database revealed protein interactions with Plcb1, Plcb2, Plcb3 and other proteins of G family such as Gnb1, Gnb2, Gnb3,Gnb4, Gng2, Gng4 and Gpsm1. KEGG pathway maps revealed interaction with eNOS, iNOS, VEGF and MAPK, which are reported to be transcribed in response to heat stress. Thus, caprine GNAI3 can be used as a possible biomarker for studying heattolerance mechanism in goats.

Correlation among hydrophobic aromatic and aliphatic residues in the six enzyme classes

Hydrophobic force as one of the fundamental forces contributes in folding of the primary sequence of amino acids into a functional three dimensional protein structure. Hydrophobic interactions of side-chains provide maximum stability to correctly folded proteins. Earlier, the authors identified the aromatic and aliphatic residues contributing maximum and minimum hydrophobicity in all the six enzyme classes. The present investigation examines the relative contributions towards hydrophobicity of the different hydrophobic amino acids in both aromatic and aliphatic categories. Notably in a sequence, inverse relationship between residues of similar hydrophobic strength both in aromatic and aliphatic categories seems to exist. This analysis is likely to provide insight for finer analysis of the enzyme molecule.

Correlation among hydrophobic aromatic and aliphatic residues in the six enzyme classes

Hydrophobic force as one of the fundamental forces contributes in folding of the primary sequence of amino acids into a functional three dimensional protein structure. Hydrophobic interactions of side-chains provide maximum stability to correctly folded proteins. Earlier, the authors identified the aromatic and aliphatic residues contributing maximum and minimum hydrophobicity in all the six enzyme classes. The present investigation examines the relative contributions towards hydrophobicity of the different hydrophobic amino acids in both aromatic and aliphatic categories. Notably in a sequence, inverse relationship between residues of similar hydrophobic strength both in aromatic and aliphatic categories seems to exist. This analysis is likely to provide insight for finer analysis of the enzyme molecule.

Immunogenicity of a recombinant fusion construct composed of intrinsically unstructured, low polymorphic segments derived from merozoite surface protein 2 and trophozoite exported protein 1

To overcome the extensive polymorphism found in human Plasmodium antigens and to avoid the lengthy characterization of their 3 dimensional structure and subsequent production of the native proteins we have been concentrated in large unstructured, non-or low-polymorphic fragments present in the blood stage of P. falciparum. Three fragments derived from the 2 family-specific and constant regions of merozoite surface protein (MSP2) and PFF0165c protein were previously selected for evaluation as potential single vaccine candidates. In order to increase and optimize their potential efficacy against P. falciparum infection the 3 antigens were combined in a single DNA recombinant product (FusN) and compared its antigenicity with that of single antigens in sera of volunteers living in endemic countries. Immunogenicity of the FusN was then compared with that of the mixture of 3 antigens in 3 strains of mice. Antigen specific, affinity purified human antibodies were then tested in antibody dependent cellular inhibition and merozoite opsonization assays. In addition, the antigen specific antibody response and its association with protection from malaria infection were determined. The data collected indicate that the recombinant product is an equal or better antigen /immunogen than fragments used either alone or as a mixture for vaccination in combination with adjuvant. In addition, antibody response to FusN shows a stronger association with protection than single fragments. The use of a single construct as vaccine would drastically reduce the cost of manufacturing and development of the GMP product.

Leveraging structural relationships as a novel mode of viral classification

100 years have passed since the independent discovery of the humble bacteriophage (phage) by Frederick Twort and Felix d’Herelle in 1915 and 1917 respectively, and since then, it has become commonly accepted that phages represent the most abundant biological entities on Earth. Despite this fact, viral taxonomy lies in extremely treacherous waters, ever changing to accommodate the next series of phylogenetic mysteries. The utilisation of genes such as the terminase large sub-unit can in some cases provide a robust taxonomic marker, but this is often found to fail at higher taxonomic levels. In addition, the rapid evolutionary dynamics and highly modular nature of phages provide yet more phylogenetic roadblocks, necessitating additional and multifaceted approaches as a means of resolution. Here, we describe a novel approach towards the taxonomic classification of phage systems. Tools for accurately predicting the three dimensional structure of proteins are improving at an unprecedented rate due to the fact that the number of protein sequences far exceeds the number of experimentally determined structures. Our approach leverages these methods through a pipeline which compares models of phage marker genes in order to permit the inference of phylogenetic relationships based on cross model superimposition. We hope this method will supplement other approaches in providing a more holistic approach to viral classification.

In silico analysis of caprine superoxide dismutase 1 (SOD1) gene

Climatic change induced heat stress causes a formidable challenge for maintaining optimum productivity in goats. The SOD1 gene (superoxide dismutase 1) is one of the genes that regulates the heat tolerance capacity. This study aimed to in silico characterize this gene. Sequence based phylogenetic tree analysis showed the caprine SOD1 gene has close evolutional relationship with that of sheep. STRING database reveals its interaction with SOD2 (Superoxide dismutase [Mn], mitochondrial), ATOX1 (Copper transport protein), RAC1 (Ras-related C3 botulinum toxin substrate 1), GPX2 (Glutathione peroxidase 2), GPX4 (Glutathione peroxidase 4), GPX5, GPX6, CAT (Catalase). The KEGG pathway maps gave interaction with eNOS, iNOS, VEGF and MAPK in which gene transcription modulates response to heat stress. The three dimensional protein structure was predicted using Modeller, Phyre 2, and Swiss Model. Structure validation was done observing the Ramachandran Plot and Hydrophobicity Plot in Discovery Studio considering amino acid residues in favoured region.

Bioinformatics and Therapeutic Insights on Proteins in Royal Jelly

Background: To date, there is no x-ray crystallography or structures from nuclear magnetic resonance (NMR) on royal jelly proteins available in the online data banks. In addition, characterization of proteins in royal jelly is not fully accomplished to date. Although new investigations unravel novel proteins in royal jelly, the majority of a protein family is present in high amounts (80-90%). Objective: In this review, we attempted to predict the three-dimensional structure of royal jelly proteins (especially the major royal jelly proteins) to allow visualization of the four protein surface properties (aromaticity, hydrophobicity, ionizability and (hydrogen (H)-bond) by using bioinformatics tools. Furthermore, we gathered the information on available therapeutic activities of crude royal jelly and its proteins. Methods: For protein modeling, prediction and analysis, the Phyre2 web portal systematically browsed in which the modeling mode was intensive. On the other side, to build visualized understanding of surface aromaticity, hydrophobicity, ionizability and H-bond of royal jelly proteins, the Discovery Studio 4.1 (Accelrys Software Inc.) was used. Results: Our in silico study confirmed that all proteins treasure these properties, including aromaticity, hydrophobicity, ionizability and (hydrogen (H)-bond. Another finding was that newly discovered proteins in royal jelly do not belong to the major royal jelly protein group. Conclusion: In conclusion, the three dimensional structure of royal jelly proteins along with its major characteristics were successfully elucidated in this review. Further studies are warranted to elucidate the detailed physiochemical properties and pharmacotherapeutics of royal jelly proteins.

Local Similarity Matrix for Cysteine Disulfide Connectivity Prediction from Protein Sequences.

Accurately predicting three dimensional protein structures from sequences would present us with targets for drugs via molecular dynamics that would treat cancer, viral infections, and neurological diseases. These treatments would have a far reaching impact to our economy, quality of life, and society. The goal of this research was to build a data mining framework to predict cysteine connectivity in proteins from the sequence and oxidation state of cysteines. Accurately predicting the cysteine bonding configuration improves the TM-Score, a quantitative measurement of protein structure prediction accuracy. We provided state of the art Qp and Qc on the PDBCYS and IVD-54 Datasets. Furthermore, we have produced a Local Similarity Matrix that compares favorably to the default PSSMs generated from PSI-Blast in a statistically significant way. Our Qp for SP39, PDBCYS, and IVD-54 were 90.6, 80.6, and 68.5, respectively.

Bioinformatics approach toward the Identification of Binding Pockets of Rice Metallothionein and its interaction with the heavy metals

Rice is a staple crop that is consumed by half of the world’s population. Paddy rice is highly prone to heavy metal toxicity. Low level of heavy metals in rice plant is beneficial for plant growth but its excess can affect the growth of the plant. Consumption of rice contaminated with heavy metal has a potential health risk to human population. Metallothionein (MT) is a metal binding proteins that comes under a class of conserved evolutionary protein molecules. It plays an essential function in the detoxification of heavy metals and homeostasis. Metals with relatively high densities, atomic weights, or atomic numbers are known as heavy metals. Cadmium (Cd), arsenic (As), chromium (Cr), lead (Pb) and zinc (Zn) are highly reactive and toxic to living cells. Plants have described two basic mechanisms such as chelation and sequestration of heavy metals by ligands to counter this problem. The two best-characterized heavy metal-binding ligands in plant cells are the phytochelatins and metallothionein. In the current study, we have generated the three dimensional structure of rice MT protein, identification of active sites of metallothionein and docking study was performed. Homology model of the metallothionein was designed through Phyre2 server. Heavy metals were docked with the metallothionein. The docking analysis and active sites were predicted through iGemDock software. The stable homology structure of the metallothionein was modelled and binding pockets were analyzed. This analysis of binding pocket will help in the in vitro study of metallothionein protein and understanding its role in metal detoxification.