Soumalee Basu
West Bengal University of Technology
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Featured researches published by Soumalee Basu.
international conference on bioinformatics | 2009
Aditi Maulik; Hiren Ghosh; Soumalee Basu
BackgroundThe PolyGalacturonase-Inhibiting Proteins (PGIP) of plant cell wall limit the invasion of phytopathogenic organisms by interacting with the enzyme PolyGalacturonase (PG) they secrete to degrade pectin present in the cell walls. PGIPs from different or same plant differ in their inhibitory activity towards the same PG. PGIP2 from Phaseolus vulgaris (Pv) inhibits the PG from Fusarium moniliforme (Fm) although PGIP1, another member of the multigene family from the same plant sharing 99% sequence similarity, cannot. Interestingly, PGIP3 from Glycine max (Gm) which is a homologue of PGIP2 is capable of inhibiting the same PG although the extent of similarity is lower and is 88%. It therefore appears that subtle changes in the sequence of plant PGIPs give rise to different specificity for inhibiting pathogenic PGs and there exists no direct dependence of function on the extent of sequence similarity.ResultsStructural information for any PGIP-PG complex being absent, we resorted to molecular modelling to gain insight into the mechanism of recognition and discrimination of PGs by PGIPs. We have built homology models of Pv PGIP1 and Gm PGIP3 using the crystal structure of Pv PGIP2 (1OGQ) as template. These PGIPs were then docked individually to Fm PG to elucidate the characteristics of their interactions. The mode of binding for Pv PGIP1 to Fm PG considerably differs from the mode observed for Pv PGIP2-Fm PG complex, regardless of the high sequence similarity the two PGIPs share. Both Pv PGIP2 and Gm PGIP3 despite being relatively less similar, interact with residues of Fm PG that are known from mutational studies to constitute the active site of the enzyme. Pv PGIP1 tends to interact with residues not located at the active site of Fm PG. Looking into the electrostatic potential surface for individual PGIPs, it was evident that a portion of the interacting surface for Pv PGIP1 differs from the corresponding region of Pv PGIP2 or Gm PGIP3.Conclusionvan der Waals and eletrostatic interactions play an active role in PGIPs for proper recognition and discrimination of PGs. Docking studies reveal that Pv PGIP2 and Gm PGIP3 interact with the residues constituting the active site of Fm PG with implications that the proteins bind/block Fm PG at its active site and thereby inhibit the enzyme.
Neurochemistry International | 2011
Sandipan Chakraborty; Sanjay Kumar; Soumalee Basu
BACE1 is a key protease involved in the proteolysis of amyloid precursor protein (APP) that generates a toxic peptide amyloid beta (Aβ), a pathological feature of Alzheimers disease (AD). The enzyme is believed to possess an open and a closed conformation that corresponds to its free and inhibitor-bound form respectively. Here, we study the dynamic transition of BACE1 employing normal mode analysis (NMA) using a simplified elastic network model (ENM). Estimation of the catalytic cavity volume on the structures of BACE1 encoded by the lowest frequency normal mode reveals the dynamical transition of the enzyme from the open to the closed conformer. Detailed analysis reveals that concerted movement of different loop segments in the active site of the protein, namely flap regions, 10s loop, A loop and F loop, squeeze the catalytic cavity between the N-terminal and C-terminal lobe of the substrate binding domain of BACE1. We also propose that the NMA encoded multiple receptor conformations (MRC) of BACE1 elucidate the pharmacophoric feature necessary to inhibit the enzyme by a polyphenol, myricetin. van der Waals interaction is found to be the main driving force that guides the ligand induced conformational switching to the closed conformer. We suggest that NMA derived MRC of BACE1 is an efficient way to treat the receptor flexibility in docking and thus can be further applied in virtual screening and structure based drug design.
Biophysical Chemistry | 2012
Sandipan Chakraborty; Barnali Chatterjee; Soumalee Basu
A collective approach of sequence analysis, phylogenetic tree and in silico prediction of amyloidogenecity using bioinformatics tools have been used to correlate the observed species-specific variations in IAPP sequences with the amyloid forming propensity. Observed substitution patterns indicate that probable changes in local hydrophobicity are instrumental in altering the aggregation propensity of the peptide. In particular, residues at 17th, 22nd and 23rd positions of the IAPP peptide are found to be crucial for amyloid formation. Proline25 primarily dictates the observed non-amyloidogenecity in rodents. Furthermore, extensive molecular dynamics simulation of 0.24 μs have been carried out with human IAPP (hIAPP) fragment 19-27, the portion showing maximum sequence variation across different species, to understand the native folding characteristic of this region. Principal component analysis in combination with free energy landscape analysis illustrates a four residue turn spanning from residue 22 to 25. The results provide a structural insight into the intramolecular β-sheet structure of amylin which probably is the template for nucleation of fibril formation and growth, a pathogenic feature of type II diabetes.
BMC Genomics | 2010
Sumana Banerjee; Soumalee Basu; Srimonti Sarkar
BackgroundPhosphatidylinositol 3-phosphate is involved in regulation of several key cellular processes, mainly endocytosis, signaling, nuclear processes, cytoskeletal remodelling, cell survival, membrane trafficking, phagosome maturation and autophagy. In most cases effector proteins bind to this lipid, using either FYVE or PX domain. These two domains are distributed amongst varied life forms such as virus, protists, fungi, viridiplantae and metazoa. As the binding ligand is identical for both domains, the goal of this study was to understand if there is any selectivity for either of these domains in different taxa. Further, to understand the different cellular functions that these domains may be involved in, we analyzed the taxonomic distribution of additional domains that associate with FYVE and PX.ResultsThere is selectivity for either FYVE or PX in individual genomes where both domains are present. Fungi and metazoa encode more PX, whereas streptophytes in viridiplantae encode more FYVE. Excess of FYVE in streptophytes results from proteins containing RCC1and DZC domains and FYVE domains in these proteins have a non-canonical ligand-binding site. Within a taxonomic group the selected domain associates with a higher number of other domains and is thus expected to discharge a larger number of cellular functions. Also, while certain associated domains are present in all taxonomic groups, most of them are unique to a specific group indicating that while certain common functions are discharged by these domains in all taxonomic groups, some functions appear to be group specific.ConclusionsAlthough both FYVE and PX bind to PtdIns(3)P, genomes of different taxa show distinct selectivity of encoding either of the two. Higher numbers of taxonomic group specific domains co-occur with the more abundant domain (FYVE/PX) indicating that group-specific rare domain architectures might have emerged to accomplish certain group-specific functions.
Chemical Biology & Drug Design | 2013
Sandipan Chakraborty; Barnali Mukherjee; Soumalee Basu
Human islet amyloid polypeptide (hIAPP) is highly amyloidogenic, whereas its homologs in rodents are non‐amyloidogenic. This observed non‐amyloidogenecity of rodent IAPP has been attributed to substitutions by proline in a region of IAPP that forms the core of the fibril. By employing molecular dynamics simulation, we have analyzed effects of position‐specific proline substitution on amyloidogenesis of the core region of the hIAPP fibril (22–28). We depict that substitution to proline at the 25th position is primarily responsible for the loss of amyloidogenecity of the peptide. In addition, 25th and 26th double mutation to proline and valine has been observed to show significant fibril destabilizing ability. On the contrary, substitution at 28th position to proline has the least ability to destabilize the amyloid fibril. Results obtained from this study are particularly important to design variants of the existing antihyperglycemic drug with minimalistic mutation approach for use in patients with diabetes.
Proteins | 2013
Aditi Maulik; Soumalee Basu
Polygalacturonase inhibiting proteins (PGIPs) are leucine‐rich repeat (LRR) proteins from plants that are organized into multigene families. They act as specific inhibitors against Polygalacturonases (PGs) from phytopathogens and share high sequence identity within species. We performed in silico mutation (Q224K and V152G) in PGIP2 from Phaseolus vulgaris to corresponding residues of another member, PGIP1. This mutation is known to cause 100% loss of inhibition against the PG of fungus Fusarium phyllophilum (Fp). A comparative analysis between PGIP2 and the double mutant, using 50 ns molecular dynamics simulations explored structural difference affecting PG binding properties. Simulations revealed that the mutation at 224, strains this residue which acts as a lock for the PGIP‐PG complex through main chain H‐bond. Changes in secondary structural elements and strain in the bend region along the convex face of the solenoidal protein affected the flexibility of the mutant protein. At the concave interacting face of the mutant, subtle changes in the sidechain behavior of the PG‐binding residues occurred in a concerted manner revealing flipping of aromatic rings to be crucial to avoid steric clash with FpPG in PGIP2. Docking PGIP2 and the mutant protein individually to FpPG illustrated the inability of the latter to inhibit FpPG leaving its active site free. Our study demonstrates that the effect of mutation affects the flexibility of the protein along the convex face, while binding specificity is altered through the concave face imparting minimal change in the typical structure supported by the LRRs. Proteins 2013.
Biophysical Reviews and Letters | 2007
Ansuman Lahiri; Soumalee Basu
We have studied the collective dynamics of leucine-rich repeat (LRR) proteins using an elastic network approximation. The slowest mode of the porcine ribonuclease inhibitor (pRI) protein could be visualized as bending fluctuations of a curved elastic strip leading to a planar opening–closing motion of the horseshoe which largely corresponded to the deformation of the protein on ligand binding. The second slowest mode however exhibited a significant out of plane splaying. The distribution of the lowest eigenvalues of different LRR proteins as a function of their repeat number was found to be close to the dispersion curve obtained from pRI whereas that of the leucine-rich variant (LRV) protein showed considerable deviation. The differing mechanical properties of these structurally similar solenoid proteins may have relevance to their function.
Central nervous system agents in medicinal chemistry | 2015
Sucharita Das; Sandipan Chakraborty; Soumalee Basu
BACE1, the aspartate protease that generates amyloid-β peptide (Aβ) in the brain of AD (Alzheimers disease) patients, has emerged as a pharmaceutically relevant target. Here, a fragment-based in silico approach has been adopted to design novel compounds with increased ligand efficiency for BACE1, before screening for brain permeability and toxicity. Fragments docked to the active site of BACE1 and sorted into two groups using binding energy cut-off, were joined to create novel ligands with binding energy lying in the range between -11.36 kcal/mol and -8.56 kcal/mol. Interestingly, QIN, a known inhibitor of BACE1 with an IC50 of 11nM, when docked to BACE1, shows a binding energy (-9.43 kcal/mol) lying within the range of the novel ligand-BACE1 complexes. The present strategy thus enabled the design of four novel inhibitors of BACE1 with favourable binding energy, brain permeability and no toxicity that might show promise as leads in future.
Journal of Molecular Structure | 2010
Sandipan Chakraborty; Soumalee Basu; Ansuman Lahiri; Soumen Basak
Carbohydrate Polymers | 2014
Sandipan Chakraborty; Soumalee Basu; Soumen Basak