<?xml version="1.0" encoding="UTF-8"?><xml><records><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Kumar, Kapil</style></author><author><style face="normal" font="default" size="100%">Patel, Krunal</style></author><author><style face="normal" font="default" size="100%">Agrawal, Dinesh C.</style></author><author><style face="normal" font="default" size="100%">Khire, Jayant Malhar</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Insights into the unfolding pathway and identification of thermally sensitive regions of phytase from aspergillus niger by molecular dynamics simulations</style></title><secondary-title><style face="normal" font="default" size="100%">Journal of Molecular Modeling</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Conformational dynamics</style></keyword><keyword><style  face="normal" font="default" size="100%">Molecular dynamics simulations</style></keyword><keyword><style  face="normal" font="default" size="100%">PhytaseA</style></keyword><keyword><style  face="normal" font="default" size="100%">Structurally weak regions</style></keyword><keyword><style  face="normal" font="default" size="100%">Thermostability</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2015</style></year><pub-dates><date><style  face="normal" font="default" size="100%">JUN</style></date></pub-dates></dates><number><style face="normal" font="default" size="100%">6</style></number><publisher><style face="normal" font="default" size="100%">SPRINGER</style></publisher><pub-location><style face="normal" font="default" size="100%">233 SPRING ST, NEW YORK, NY 10013 USA</style></pub-location><volume><style face="normal" font="default" size="100%">21</style></volume><pages><style face="normal" font="default" size="100%">UNSP 163</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;Thermal stability is of great importance in the application of commercial phytases. Phytase A (PhyA) is a monomeric protein comprising twelve alpha-helices and ten beta-sheets. Comparative molecular dynamics (MD) simulations (at 310, 350, 400, and 500 K) revealed that the thermal stability of PhyA from Aspergillus niger (A. niger) is associated with its conformational rigidity. The most thermally sensitive regions were identified as loops 8 (residues 83-106), 10 (161174), 14 (224-230), 17 (306-331), and 24 (442-444), which are present on the surface of the protein. It was observed that solvent-exposed loops denature before or show higher flexibility than buried residues. We observed that PhyA begins to unfold at loops 8 and 14, which further extends to loop 24 at the C-terminus. The intense movement of loop 8 causes the helix H2 and beta-sheet B3 to fluctuate at high temperature. The high flexibility of the H2, H10, and H12 helices at high temperature resulted in complete denaturation. The high mobility of loop 14 easily transfers to the adjacent helices H7, H8, and H9, which fluctuate and partially unfold at high temperature (500 K). It was also observed that the salt bridges Asp110-Lys149, Asp205-Lys277, Asp335-Arg136, Asp416-Arg420, and Glu387-Arg400 are important influences on the structural stability but not the thermostability, as the lengths of these salt bridges did not increase with rising temperature. The salt bridges Glu125-Arg163, Asp299-Arg136, Asp266-Arg219, Asp339-Lys278, Asp335-Arg136, and Asp424-Arg428 are all important for thermostability, as the lengths of these bridges increased dramatically with increasing temperature. Here, for the first time, we have computationally identified the thermolabile regions of PhyA, and this information could be used to engineer novel thermostable phytases. Numerous homologous phytases of fungal as well as bacterial origin are known, and these homologs show high sequence similarity. Our findings could prove useful in attempts to increase the thermostability of homologous phytases via protein engineering.&lt;/p&gt;</style></abstract><issue><style face="normal" font="default" size="100%">6</style></issue><custom3><style face="normal" font="default" size="100%">&lt;p&gt;Foreign&lt;/p&gt;</style></custom3><custom4><style face="normal" font="default" size="100%">1.438</style></custom4></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Sandholu, Anand S.</style></author><author><style face="normal" font="default" size="100%">Mohole, Madhura</style></author><author><style face="normal" font="default" size="100%">Duax, William L.</style></author><author><style face="normal" font="default" size="100%">Thulasiram, Hirekodathakallu V.</style></author><author><style face="normal" font="default" size="100%">Sengupta, Durba</style></author><author><style face="normal" font="default" size="100%">Kulkarni, Kiran</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Dynamics of loops at the substrate entry channel determine the specificity of iridoid synthases</style></title><secondary-title><style face="normal" font="default" size="100%">Febs Letters</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">iridoid synthase</style></keyword><keyword><style  face="normal" font="default" size="100%">iridoids</style></keyword><keyword><style  face="normal" font="default" size="100%">Molecular dynamics simulations</style></keyword><keyword><style  face="normal" font="default" size="100%">progesterone 5 beta-reductase</style></keyword><keyword><style  face="normal" font="default" size="100%">Substrate specificity</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2018</style></year><pub-dates><date><style  face="normal" font="default" size="100%">AUG</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">592</style></volume><pages><style face="normal" font="default" size="100%">2624-2635</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;Iridoid synthases belong to the family of short-chain dehydrogenase reductase involved in the biosynthesis of iridoids. Despite having high sequence and structural homology with progesterone 5 beta- reductase, these enzymes exhibit differential substrate specificities. Previously, two loops. L1 and L2 at substrate-binding pocket, were suggested to be involved in generating substrate specificity. However, the structural basis of specificity determinants was elusive. Here, combining sequence and structural analysis, site-directed mutagenesis, and molecular dynamics simulations, we have shown that iridoid synthase contains two channels for substrate entry whose geometries are altered by L1-L2 dynamics, primarily orchestrated by interactions of residues Glu161 and Gly162 of L1 and Asn358 of L2. A complex interplay of these interactions confer the substrate specificity to the enzyme.&lt;/p&gt;</style></abstract><issue><style face="normal" font="default" size="100%">15</style></issue><custom3><style face="normal" font="default" size="100%">Foreign</style></custom3><custom4><style face="normal" font="default" size="100%">3.623</style></custom4></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Roy, Debopriya</style></author><author><style face="normal" font="default" size="100%">Sengupta, Durba</style></author><author><style face="normal" font="default" size="100%">Kulkarni, Kiran</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Substrate induced dynamical remodeling of the binding pocket generates GTPase specificity in DOCK family of guanine nucleotide exchange factors</style></title><secondary-title><style face="normal" font="default" size="100%">Biochemical and Biophysical Research Communications</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Dedicator of cytokinesis</style></keyword><keyword><style  face="normal" font="default" size="100%">GTPase specificity</style></keyword><keyword><style  face="normal" font="default" size="100%">Guanine exchange factors</style></keyword><keyword><style  face="normal" font="default" size="100%">Molecular dynamics simulations</style></keyword><keyword><style  face="normal" font="default" size="100%">Mutual information</style></keyword><keyword><style  face="normal" font="default" size="100%">Rho GTPases</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2022</style></year><pub-dates><date><style  face="normal" font="default" size="100%">NOV</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">631</style></volume><pages><style face="normal" font="default" size="100%">32-40</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;
	Dedicator of cytokinesis (DOCK) family of guanine nucleotide exchange factors (GEFs) activate two members of Rho family GTPases, Rac1/Cdc42, to exert diverse cellular processes, including cell migration. As DOCK GEFs have been critically implicated in tumour cell migration, understanding their function and specificity is imperative for designing anti-metastatic drugs. Based on their GTPase specificity they have been classified as Rac, Cdc42 and dual specific GEFs. Despite extensive structural studies, the factors that determine GTPase specificity of DOCK GEFs have remained elusive. Here, we show that subtle dynamical coupling between GEF and GTPase structures modulate the binding interface to generate mutual spec-ificity. To cluster the dynamically coupled residues in GEF-GTPase complexes a novel intra-residue backbone-torsion-angles based mutual information (TMI) technique was employed. TMI was calcu-lated from 4500 trajectories obtained from a total of 4.5ms molecular dynamics simulations performed on members of all the three clades of DOCK GEFs. The obtained clusters suggest a specificity generation mechanism that involves optimization of the binding pocket for the crucial divergent residue at the 56th position of Rac/Cdc42 (FCdc42/WRac1). These clusters encompass five residues from the structural segment lobe C -a10 helix of the DOCK proteins and functional SWI region of GTPase, which induce orchestrated structural modulations to generate the specificity. Even the conserved residues from SWI region are seen to augment the specificity defining dynamical rearrangements. Furthermore, the pro-posed dynamical GTPase-DOCK GEF specificity model was verified using mutagenesis studies on Rac1 and dual GTPase specific Dock2 and Dock6, respectively. Thus the current study provides the generic substrate specificity determinants of DOCK GEFs, which are not apparent from the conventional struc-tural analysis.(c) 2022 Elsevier Inc. All rights reserved.&lt;/p&gt;
</style></abstract><work-type><style face="normal" font="default" size="100%">Article</style></work-type><custom3><style face="normal" font="default" size="100%">&lt;p&gt;
	Foreign&lt;/p&gt;
</style></custom3><custom4><style face="normal" font="default" size="100%">&lt;p&gt;
	3.322&lt;/p&gt;
</style></custom4></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Prakash, Shikha</style></author><author><style face="normal" font="default" size="100%">Krishna, Anjali</style></author><author><style face="normal" font="default" size="100%">Sengupta, Durba</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Cofilin-membrane interactions: electrostatic effects in phosphoinositide lipid binding</style></title><secondary-title><style face="normal" font="default" size="100%">ChemPhysChem</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">complex membrane</style></keyword><keyword><style  face="normal" font="default" size="100%">lipid clustering</style></keyword><keyword><style  face="normal" font="default" size="100%">Martini coarse-grain simulations</style></keyword><keyword><style  face="normal" font="default" size="100%">Molecular dynamics simulations</style></keyword><keyword><style  face="normal" font="default" size="100%">Protein-lipid interactions</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2023</style></year><pub-dates><date><style  face="normal" font="default" size="100%">FEB </style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">24</style></volume><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;
	The actin cytoskeleton interacts with the cell membrane primarily through the indirect interactions of actin-binding proteins such as cofilin-1. The molecular mechanisms underlying the specific interactions of cofilin-1 with membrane lipids are still unclear. Here, we performed coarse-grain molecular dynamics simulations of cofilin-1 with complex lipid bilayers to analyze the specificity of protein-lipid interactions. We observed the maximal interactions with phosphoinositide (PIP) lipids, especially PIP2 and PIP3 lipids. A good match was observed between the residues predicted to interact and previous experimental studies. The clustering of PIP lipids around the membrane bound protein leads to an overall lipid demixing and gives rise to persistent membrane curvature. Further, through a series of control simulations, we observe that both electrostatics and geometry are critical for specificity of lipid binding. Our current study is a step towards understanding the physico-chemical basis of cofilin-PIP lipid interactions.&lt;/p&gt;
</style></abstract><issue><style face="normal" font="default" size="100%">3</style></issue><work-type><style face="normal" font="default" size="100%">Article</style></work-type><custom3><style face="normal" font="default" size="100%">&lt;p&gt;
	Foreign&lt;/p&gt;
</style></custom3><custom4><style face="normal" font="default" size="100%">&lt;p&gt;
	3.520&lt;/p&gt;
</style></custom4></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Mohole, Madhura</style></author><author><style face="normal" font="default" size="100%">Naglekar, Amit</style></author><author><style face="normal" font="default" size="100%">Sengupta, Durba</style></author><author><style face="normal" font="default" size="100%">Chattopadhyay, Amitabha</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Probing the energy landscape of the lipid interactions of the serotonin 1A receptor</style></title><secondary-title><style face="normal" font="default" size="100%">Biophysical Chemistry</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">GPCR-lipid interactions</style></keyword><keyword><style  face="normal" font="default" size="100%">Lipid energetics</style></keyword><keyword><style  face="normal" font="default" size="100%">Lipid residence time</style></keyword><keyword><style  face="normal" font="default" size="100%">Molecular dynamics simulations</style></keyword><keyword><style  face="normal" font="default" size="100%">Serotonin 1 a receptor</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2024</style></year><pub-dates><date><style  face="normal" font="default" size="100%">OCT</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">313</style></volume><pages><style face="normal" font="default" size="100%">107289</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;
	G protein-coupled receptors (GPCRs) are lipid-regulated transmembrane proteins that play a central role in cell signaling and pharmacology. Although the role of membrane lipids in GPCR function is well established, the underlying GPCR-lipid interactions have not been thermodynamically characterized due to the complexity of these interactions. In this work, we estimate the energetics and dynamics of lipid association from coarse-grain simulations of the serotonin1A receptor embedded in a complex membrane. We show that lipids bind to the receptor with varying energetics of 1-4 kT, and timescales of 1-10 mu s. The most favorable energetics and longest residence times are observed for cholesterol, glycosphingolipid GM1, phosphatidylethanolamine (PE) and phosphatidylserine (PS) lipids. Multi-exponential fitting of the contact probability suggests distinct dynamic regimes, corresponding to ps, ns and mu s timescales, that we correlate with the annular, intermediate and nonannular lipid sites. The timescales of lipid binding correspond to high barrier heights, despite their relatively weaker energetics. Our results highlight that GPCR-lipid interactions are driven by both thermodynamic interactions and the dynamical features of lipid binding.&lt;/p&gt;
</style></abstract><work-type><style face="normal" font="default" size="100%">Article</style></work-type><custom3><style face="normal" font="default" size="100%">&lt;p&gt;
	Foreign&lt;/p&gt;
</style></custom3><custom4><style face="normal" font="default" size="100%">&lt;p&gt;
	3.8&lt;/p&gt;
</style></custom4></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Gharui, Sowmomita</style></author><author><style face="normal" font="default" size="100%">Sengupta, Durba</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Molecular interactions of the pioneer transcription factor GATA3 With DNA</style></title><secondary-title><style face="normal" font="default" size="100%">Proteins-Structure Function and Bioinformatics</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">DNA-protein interactions</style></keyword><keyword><style  face="normal" font="default" size="100%">GATA protein</style></keyword><keyword><style  face="normal" font="default" size="100%">Molecular dynamics simulations</style></keyword><keyword><style  face="normal" font="default" size="100%">molecular mechanism</style></keyword><keyword><style  face="normal" font="default" size="100%">population variants</style></keyword><keyword><style  face="normal" font="default" size="100%">transcription factor</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2025</style></year><pub-dates><date><style  face="normal" font="default" size="100%">FEB</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">93</style></volume><pages><style face="normal" font="default" size="100%">555-566</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;
	The GATA3 transcription factor is a pioneer transcription factor that is critical in the development, proliferation, and maintenance of several immune cell types. Identifying the detailed conformational dynamics and interactions of this transcription factor, as well as its clinically important population variants will allow us to unravel its mode of action. In this study, we analyze the molecular interactions of the GATA3 transcription factor bound to dsDNA as well as three clinically important population variants by atomistic molecular dynamics simulations. We identify the effect of the variants on the DNA conformational dynamics and delineate the differences compared to the wildtype transcription factor that could be related to impaired function. We highlight the structural plasticity in the binding of the GATA3 transcription factor and identify important DNA-protein contacts. Although the DNA-protein contacts are persistent and appear to be stable, they exhibit nanosecond timescale fluctuations and several binding/unbinding events. Further, we identify differential DNA binding in the three variants and show that the N-terminal binding is reduced in two of the variants. Our results indicate that reduced minor groove width and DNA diameter are important hallmarks for the binding of GATA3. Our work is an important step towards understanding the functional dynamics of the GATA3 protein and its clinically significant population variants.&lt;/p&gt;
</style></abstract><issue><style face="normal" font="default" size="100%">2</style></issue><work-type><style face="normal" font="default" size="100%">Article</style></work-type><custom3><style face="normal" font="default" size="100%">&lt;p&gt;
	Foreign&lt;/p&gt;
</style></custom3><custom4><style face="normal" font="default" size="100%">&lt;p&gt;
	3.2&lt;/p&gt;
</style></custom4></record></records></xml>