Dynamics of loops at the substrate entry channel determine the specificity of iridoid synthases - Sandholu, Anand S.; Mohole, Madhura; Duax, William L.; Thulasiram, Hirekodathakallu V.; Sengupta, Durba; Kulkarni, Kiran (Febs Letters, 2018)
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.
Keywords: iridoid synthase; iridoids; Molecular dynamics simulations; progesterone 5 beta-reductase; Substrate specificity

Substrate induced dynamical remodeling of the binding pocket generates GTPase specificity in DOCK family of guanine nucleotide exchange factors - Roy, Debopriya; Sengupta, Durba; Kulkarni, Kiran (Biochemical and Biophysical Research Communications, 2022)
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.
Keywords: Dedicator of cytokinesis; GTPase specificity; Guanine exchange factors; Molecular dynamics simulations; Mutual information; Rho GTPases

Cofilin-membrane interactions: electrostatic effects in phosphoinositide lipid binding - Prakash, Shikha; Krishna, Anjali; Sengupta, Durba (ChemPhysChem, 2023)
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.
Keywords: complex membrane; lipid clustering; Martini coarse-grain simulations; Molecular dynamics simulations; Protein-lipid interactions

Probing the energy landscape of the lipid interactions of the serotonin 1A receptor - Mohole, Madhura; Naglekar, Amit; Sengupta, Durba; Chattopadhyay, Amitabha (Biophysical Chemistry, 2024)
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.
Keywords: GPCR-lipid interactions; Lipid energetics; Lipid residence time; Molecular dynamics simulations; Serotonin 1 a receptor

Molecular interactions of the pioneer transcription factor GATA3 With DNA - Gharui, Sowmomita; Sengupta, Durba (Proteins-Structure Function and Bioinformatics, 2025)
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.
Keywords: DNA-protein interactions; GATA protein; Molecular dynamics simulations; molecular mechanism; population variants; transcription factor