The choice includes a selection of mature chains or peptides and domains from the Swiss-Prot feature table which can be chosen by clicking on the positions , as well as the possibility to enter start and end position in two boxes. By default i. Note: It is not possible to specify post-translational modification for your protein, nor will ProtParam know whether your mature protein forms dimers or multimers. If you do know that your protein forms a dimer, you may just duplicate your sequence i.
The parameters computed by ProtParam include the molecular weight, theoretical pI, amino acid composition, atomic composition, extinction coefficient, estimated half-life, instability index, aliphatic index and grand average of hydropathicity GRAVY. The amino acid and atomic compositions are self-explanatory. All the other parameters will be explained below.
Extinction coefficients The extinction coefficient indicates how much light a protein absorbs at a certain wavelength. It is useful to have an estimation of this coefficient for following a protein which a spectrophotometer when purifying it. It has been shown [ 1c ] that it is possible to estimate the molar extinction coefficient of a protein from knowledge of its amino acid composition. The first one shows the computed value based on the assumption that all cysteine residues appear as half cystines i.
Note: Cystine is the amino acid formed when of a pair of cysteine molecules are joined by a disulfide bond. Important note for previous users of ProtParam: Changed algorithm for Extinction coefficient We have chosen to calculate protein extinction coefficients using the Edelhoch method [ 1b ], but with the extinction coefficients for Trp and Tyr determined by Pace [ 1a ] et al.
Edelhoch determined extinction coefficients for Trp and Tyr by using blocked amino acid analogs as model substances to represent the situation in proteins.
N-acetyl-L-tryptophanamide and glycyl-L-tyrosylglycine were used for Trp and Tyr, respectively and the values were determined in pH 6. Gill and von Hippel [ 1c ] found that these values valid for calculating the extinction coefficients of the denatured protein with good approximation could also be used to calculate the extinction coefficients of the native protein.
The functions of alkaloid proteins of C. The result was presented in Table 4. The secondary structure was predicted by using default parameters window width, 17; similarity threshold, 8; and number of states, 4. The modeling of the three-dimensional structure of the protein was performed by homology modeling program, Swiss Model. The Phi and PSi distribution of the Ramachandran map generated by non-glycine, non-proline residues were summarized in Table 6 and Fig. The calculated isoelectric point pI will be useful because at pI, solubility is least and mobility in an electro-focusing system is zero.
At pI, proteins were stable and compact. The computed isoelectric point will be useful for developing a buffer system for purification by isoelectric focusing method. The instability index provides an estimate of the stability of protein in a test tube. A protein whose instability index is smaller than 40 is predicted as stable; a value above 40 predicts that the protein may be unstable [ 13 ]. The instability index value for P The aliphatic index AI which is defined as the relative volume of a protein occupied by aliphatic side chains A, V, I, and L is regarded as a positive factor for the increase of thermal stability of globular proteins.
This higher value indicates the thermal stability of the protein. The grand average hydropathy GRAVY value for a peptide or protein is calculated as the sum of hydropathy values of all the amino acids, divided by the number of residues in the sequence.
The transmembrane regions are rich in hydrophobic amino acids Table 3. Sequence of a particular cluster of residue types, which is variously known as a pattern, motif, signature, or fingerprint. These motifs, typically around 10 to 20 amino acids in length, arise because specific residues and regions thought or proved to be important to the biological function of a group of proteins are conserved in both structure and sequence during evolution [ 23 ].
Prosite analysis suggested the functionality of these proteins with profiles and patterns identified for characteristic functionality were represented in Table 4. In protein P, no motif was found in any range. The results show that random coil dominated among secondary structure elements followed by extended strand, alpha helix, and beta turns. Homology modeling is the method of choice for obtaining 3D coordinates of proteins. For the STR, experimental protein structures were searched to identify suitable templates.
On the basis of a sequence alignment between the STR and the template structure, a three-dimensional model for the STR was generated. STR catalyzes a Pictet-Spengler-type reaction and represents a novel six-bladed b-propeller fold in plant proteins [ 10 ]. STR from R. STR has been detected and biochemically characterized from cell suspension culture of apocynaceae plant C. Three-dimensional structures are predicted for proteins where such data is unavailable. There is lack of experimental structures for this protein considered.
Swiss model was used to generate the homology model for STR that has not been reported in literature yet. The protein-ligand interaction was found to be very important. Homology modeling was the most accurate computational method to generate reliable structural models. It was used in many biological applications. Model quality assessment tools were used to estimate the reliability of the models. The stereochemical quality of the predicted model and accuracy of the protein model was evaluated after the refinement process using Ramachandran map calculations computed with the PROCHECK program.
The assessment of the predicted model generated by Swiss model was shown in Fig. The main chain parameters plotted are Ramachandran plot quality, peptide bond planarity, bad non-bonded interactions, main chain hydrogen bond energy, C-alpha chirality, and overall G factor.
In the Ramachandran plot analysis, the residues were classified according to its regions in the quadrangle. The red regions in the graph indicate the most allowed regions whereas the yellow regions represent allowed regions. Glycine is represented by triangles and other residues are represented by squares. The result revealed that the modeled structure for P has Such figures assigned by Ramachandran plot represent a good quality of the predicted models. PROVE plot was used to calculate the atoms in the modeled structure of strictosidine synthase, which shows the particular result in Table 7.
The RMS Z score was found to be more than 1 that also supports good quality of model structure. In this study, STR that plays an important role in alkaloid biosynthesis of C.
Functional analysis of this protein was performed by SOSUI server which predicted the transmembrane helix. Secondary structure analysis revealed that Alpha helix dominated among secondary structure elements followed by random coil, extended strand, and beta turns. The modeling of the three-dimensional structure of the Strictosidine synthase P was performed by Swiss model.
Google Scholar. Article Google Scholar. Sarabjot Kaur, Poonam Mondal. Journal of microbiology and Experimentation. Yamazaki Y et al Metabolite profiling of alkaloids and strictosidine synthase activity in camptothecin producing plants. Phytochemistry — Kutchan, T. The Plant cell7, — Smith, G. Strictosidine: a key intermediate in the biogenesis of indole alkaloids. Kutchan TM Expression of enzymatically active cloned strictosidine synthase from the higher plant Rauvolfia serpentina in Escherichia coli.
FEBS Lett — DNA sequence determination and expression in Escherichia coli. The experiments included in Biochemistry Virtual Lab I are fundamental in nature, dealing with the identification and classification of various carbohydrates, acid-base titrations of amino acids, isolation of proteins from their natural sources, etc.
Population ecology is the study of populations especially population abundance and how they change over time. Crucial to this study are the various interactions between a population and its resources. Studies on simple models of interacting species is the main focus this simulation oriented lab. Studies based on models of predation, competition as seen in interacting species is the main focus this simulation oriented lab. Lab II focuses on applied principles of population ecology for PG students.
This includes eukaryotes such as fungi and, protists and prokaryotes. Viruses, though not strictly classed as living organisms, are also studied.
This field overlaps with other areas of biology and chemistry, particularly genetics and biochemistry. Molecular biology chiefly concerns itself with understanding the interactions between the various systems of a cell, including the interactions between DNA, RNA and protein biosynthesis as well as learning how these interactions are regulated.
It includes the study of the structure and organization, growth, regulation, movements and interaction of the cells. Cell biology is closely related to other areas of biology such as genetics, molecular biology, and biochemistry.
This virtual lab is an introductory course for undergraduate students and deals with the storage and retrieval of data from different biological databases like Gene, Pubmed, GEO, TAIR, Prosite etc. The exercises mainly deal with the different algorithms in sequence alignment and provides a computational exploration to the use of various tools used for sequence alignment. This lab is targeted towards PG students with exercises that will allow one to learn visualising proteins in 3D, how to calculate distance among atoms, find active sites in protein structures and also delve into some structural analysis methods including docking and homology modeling.
Combining labs 1, 2 and 3 will give an overall understanding of commonly used computational methods in bioinformatics. Mathematical modeling and simulating of Biochemical network Import and simulate models from different databases To Import and simulate a model from the repository SBML-A markup language for mathematical models in systems biology using cell designer Creating and Visualizing a Simple Network Model Analysis of biological networks for feature detection Integrating Biological Networks and Microarray Expression data Analyzing the network by finding sub modules Computer-Aided Drug Design Virtual Lab This lab is for PG students on the various laboratory topics in computer-aided drug design.
Constructing computational model of a molecule Introducing Hydrogen atoms to a molecule Dihedral angle calculation of a molecule Energy minimization of a molecule Predict the structure of protein-Homology Modeling Drug-Receptor Interaction Absorption and Distribution Property Prediction in Drug Designing Process Toxicity prediction of a Molecule Ecology Virtual Lab Ecosystems are a complex and delicate balancing game.
Ecosystems have an extremely complex web of cause and effect.
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