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Dive into the research topics where Srayanta Mukherjee is active.

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Featured researches published by Srayanta Mukherjee.


Structure | 2011

Protein-Protein Complex Structure Predictions by Multimeric Threading and Template Recombination

Srayanta Mukherjee; Yang Zhang

The total number of protein-protein complex structures currently available in the Protein Data Bank (PDB) is six times smaller than the total number of tertiary structures in the PDB, which limits the power of homology-based approaches to complex structure modeling. We present a threading-recombination approach, COTH, to boost the protein complex structure library by combining tertiary structure templates with complex alignments. The query sequences are first aligned to complex templates using a modified dynamic programming algorithm, guided by ab initio binding-site predictions. The monomer alignments are then shifted to the multimeric template framework by structural alignments. COTH was tested on 500 nonhomologous dimeric proteins, which can successfully detect correct templates for 50% of the cases after homologous templates are excluded, which significantly outperforms conventional homology modeling algorithms. It also shows a higher accuracy in interface modeling than rigid-body docking of unbound structures from ZDOCK although with lower coverage. These data demonstrate new avenues to model complex structures from nonhomologous templates.


Nucleic Acids Research | 2009

MM-align: a quick algorithm for aligning multiple-chain protein complex structures using iterative dynamic programming

Srayanta Mukherjee; Yang Zhang

Structural comparison of multiple-chain protein complexes is essential in many studies of protein–protein interactions. We develop a new algorithm, MM-align, for sequence-independent alignment of protein complex structures. The algorithm is built on a heuristic iteration of a modified Needleman–Wunsch dynamic programming (DP) algorithm, with the alignment score specified by the inter-complex residue distances. The multiple chains in each complex are first joined, in every possible order, and then simultaneously aligned with cross-chain alignments prevented. The alignments of interface residues are enhanced by an interface-specific weighting factor. MM-align is tested on a large-scale benchmark set of 205 × 3897 non-homologous multiple-chain complex pairs. Compared with a naïve extension of the monomer alignment program of TM-align, the alignment accuracy of MM-align is significantly higher as judged by the average TM-score of the physically-aligned residues. MM-align is about two times faster than TM-align because of omitting the cross-alignment zone of the DP matrix. It also shows that the enhanced alignment of the interfaces helps in identifying biologically relevant protein complex pairs.


Journal of Proteome Research | 2011

Functional implications of structural predictions for alternative splice proteins expressed in Her2/neu-induced breast cancers.

Rajasree Menon; Ambrish Roy; Srayanta Mukherjee; Saveliy Belkin; Yang Zhang; Gilbert S. Omenn

Alternative splicing allows a single gene to generate multiple mRNA transcripts, which can be translated into functionally diverse proteins. However, experimentally determined structures of protein splice isoforms are rare, and homology modeling methods are poor at predicting atomic-level structural differences because of high sequence identity. Here we exploit the state-of-the-art structure prediction method I-TASSER to analyze the structural and functional consequences of alternative splicing of proteins differentially expressed in a breast cancer model. We first successfully benchmarked the I-TASSER pipeline for structure modeling of all seven pairs of protein splice isoforms, which are known to have experimentally solved structures. We then modeled three cancer-related variant pairs reported to have opposite functions. In each pair, we observed structural differences in regions where the presence or absence of a motif can directly influence the distinctive functions of the variants. Finally, we applied the method to five splice variants overexpressed in mouse Her2/neu mammary tumor: anxa6, calu, cdc42, ptbp1, and tax1bp3. Despite >75% sequence identity between the variants, structural differences were observed in biologically important regions of these protein pairs. These results demonstrate the feasibility of integrating proteomic analysis with structure-based conformational predictions of differentially expressed alternative splice variants in cancers and other conditions.


PLOS ONE | 2012

How Many Protein-Protein Interactions Types Exist in Nature?

Leonardo D. Garma; Srayanta Mukherjee; Pralay Mitra; Yang Zhang

“Protein quaternary structure universe” refers to the ensemble of all protein-protein complexes across all organisms in nature. The number of quaternary folds thus corresponds to the number of ways proteins physically interact with other proteins. This study focuses on answering two basic questions: Whether the number of protein-protein interactions is limited and, if yes, how many different quaternary folds exist in nature. By all-to-all sequence and structure comparisons, we grouped the protein complexes in the protein data bank (PDB) into 3,629 families and 1,761 folds. A statistical model was introduced to obtain the quantitative relation between the numbers of quaternary families and quaternary folds in nature. The total number of possible protein-protein interactions was estimated around 4,000, which indicates that the current protein repository contains only 42% of quaternary folds in nature and a full coverage needs approximately a quarter century of experimental effort. The results have important implications to the protein complex structural modeling and the structure genomics of protein-protein interactions.


Protein Science | 2013

Three dimensional structure of the anthrax toxin translocon–lethal factor complex by cryo‐electron microscopy

Edward P. Gogol; Narahari Akkaladevi; L. Szerszen; Srayanta Mukherjee; L. Chollet-Hinton; Hiroo Katayama; Brad L. Pentelute; R. J. Collier; Mark T. Fisher

We have visualized by cryo‐electron microscopy (cryo‐EM) the complex of the anthrax protective antigen (PA) translocon and the N‐terminal domain of anthrax lethal factor (LFN) inserted into a nanodisc model lipid bilayer. We have determined the structure of this complex at a nominal resolution of 16 Å by single‐particle analysis and three‐dimensional reconstruction. Consistent with our previous analysis of negatively stained unliganded PA, the translocon comprises a globular structure (cap) separated from the nanodisc bilayer by a narrow stalk that terminates in a transmembrane channel (incompletely distinguished in this reconstruction). The globular cap is larger than the unliganded PA pore, probably due to distortions introduced in the previous negatively stained structures. The cap exhibits larger, more distinct radial protrusions, previously identified with PA domain three, fitted by elements of the NMFF PA prepore crystal structure. The presence of LFN, though not distinguished due to the seven‐fold averaging used in the reconstruction, contributes to the distinct protrusions on the cap rim volume distal to the membrane. Furthermore, the lumen of the cap region is less resolved than the unliganded negatively stained PA, due to the low contrast obtained in our images of this specimen. Presence of the LFN extended helix and N terminal unstructured regions may also contribute to this additional internal density within the interior of the cap. Initial NMFF fitting of the cryoEM‐defined PA pore cap region positions the Phe clamp region of the PA pore translocon directly above an internal vestibule, consistent with its role in toxin translocation.


Protein Science | 2013

Assembly of anthrax toxin pore: Lethal-factor complexes into lipid nanodiscs

Narahari Akkaladevi; L. Hinton-Chollet; Hiroo Katayama; J. Mitchell; L. Szerszen; Srayanta Mukherjee; Edward P. Gogol; Brad L. Pentelute; R. J. Collier; Mark T. Fisher

We have devised a procedure to incorporate the anthrax protective antigen (PA) pore complexed with the N‐terminal domain of anthrax lethal factor (LFN) into lipid nanodiscs and analyzed the resulting complexes by negative‐stain electron microscopy. Insertion into nanodiscs was performed without relying on primary and secondary detergent screens. The preparations were relatively pure, and the percentage of PA pore inserted into nanodiscs on EM grids was high (∼43%). Three‐dimensional analysis of negatively stained single particles revealed the LFN‐PA nanodisc complex mirroring the previous unliganded PA pore nanodisc structure, but with additional protein density consistent with multiple bound LFN molecules on the PA cap region. The assembly procedure will facilitate collection of higher resolution cryo‐EM LFN‐PA nanodisc structures and use of advanced automated particle selection methods.


Proteins | 2012

Predicting nucleic acid binding interfaces from structural models of proteins.

Iris Dror; Shula Shazman; Srayanta Mukherjee; Yang Zhang; Fabian Glaser; Yael Mandel-Gutfreund

The function of DNA‐ and RNA‐binding proteins can be inferred from the characterization and accurate prediction of their binding interfaces. However, the main pitfall of various structure‐based methods for predicting nucleic acid binding function is that they are all limited to a relatively small number of proteins for which high‐resolution three‐dimensional structures are available. In this study, we developed a pipeline for extracting functional electrostatic patches from surfaces of protein structural models, obtained using the I‐TASSER protein structure predictor. The largest positive patches are extracted from the protein surface using the patchfinder algorithm. We show that functional electrostatic patches extracted from an ensemble of structural models highly overlap the patches extracted from high‐resolution structures. Furthermore, by testing our pipeline on a set of 55 known nucleic acid binding proteins for which I‐TASSER produces high‐quality models, we show that the method accurately identifies the nucleic acids binding interface on structural models of proteins. Employing a combined patch approach we show that patches extracted from an ensemble of models better predicts the real nucleic acid binding interfaces compared with patches extracted from independent models. Overall, these results suggest that combining information from a collection of low‐resolution structural models could be a valuable approach for functional annotation. We suggest that our method will be further applicable for predicting other functional surfaces of proteins with unknown structure. Proteins 2012.


Bioinformatics | 2015

GS-align for glycan structure alignment and similarity measurement

Hui Sun Lee; Sunhwan Jo; Srayanta Mukherjee; Sang-Jun Park; Jeffrey Skolnick; Jooyoung Lee; Wonpil Im

MOTIVATION Glycans play critical roles in many biological processes, and their structural diversity is key for specific protein-glycan recognition. Comparative structural studies of biological molecules provide useful insight into their biological relationships. However, most computational tools are designed for protein structure, and despite their importance, there is no currently available tool for comparing glycan structures in a sequence order- and size-independent manner. RESULTS A novel method, GS-align, is developed for glycan structure alignment and similarity measurement. GS-align generates possible alignments between two glycan structures through iterative maximum clique search and fragment superposition. The optimal alignment is then determined by the maximum structural similarity score, GS-score, which is size-independent. Benchmark tests against the Protein Data Bank (PDB) N-linked glycan library and PDB homologous/non-homologous N-glycoprotein sets indicate that GS-align is a robust computational tool to align glycan structures and quantify their structural similarity. GS-align is also applied to template-based glycan structure prediction and monosaccharide substitution matrix generation to illustrate its utility. AVAILABILITY AND IMPLEMENTATION http://www.glycanstructure.org/gsalign. CONTACT [email protected] SUPPLEMENTARY INFORMATION Supplementary data are available at Bioinformatics online.


Archive | 2011

Genome-Wide Protein Structure Prediction

Srayanta Mukherjee; András Szilágyi; Ambrish Roy; Yang Zhang

The post-genomic era has witnessed an explosion of protein sequences in the public databases; but this has not been complemented by the availability of genome-wide structure and function information, due to the technical difficulties and labor expenses incurred by existing experimental techniques. The rapid advancements in computer-based protein structure prediction methods have enabled automated and yet reliable methods for generating three-dimensional (3D) structural models of proteins. Genome-scale structure prediction experiments have been conducted by a number of groups, starting as early as in 1997, and some noteworthy efforts have been made using the MODELLER and ROSETTA methods. Along another line, TOUCHSTONE was used to predict the structures of all 85 small proteins in the Mycoplasma genitalium genome, which established template-refinement-based structure prediction as a practical approach for genome-scale experiments. This was followed by the development of Threading ASSEmbly Refinement (TASSER) and Iterative Threading ASSEmbly Refinement (I-TASSER) algorithms which use a combination of various approaches for threading, fragment assembly, ab initio loop modeling, and structural refinement to predict the structures. A successful structural prediction for all medium-sized open reading frames (ORFs) in the Escherichia coli genome was demonstrated by this method, achieving high-accuracy models for 920 out of 1,360 proteins. G protein-coupled receptors (GPCRs) are an extremely important class of membrane proteins for which only very few structures are available in the Protein Data Bank (PDB). TASSER was used to predict the structures of all 907 putative GPCRs in the human genome, and the high accuracy confirmed by newly solved GPCR structures and recent blind tests have demonstrated the usefulness and robustness of the TASSER/I-TASSER models for the functional annotation of GPCRs. Recently, the I-TASSER protein structure prediction method has been used as a basis for functional annotation of protein sequences. The increasing popularity and need for such automated structure and function prediction algorithms can be judged by the fact that the I-TASSER server has generated structure predictions for 35,000 proteins submitted by more than 8,000 users from 86 countries in the last 24 months. The success of these modeling experiments demonstrates significant new progress in high-throughput and genome-wide protein structure prediction.


Toxins | 2017

Asymmetric Cryo-EM Structure of Anthrax Toxin Protective Antigen Pore with Lethal Factor N-Terminal Domain

Alexandra J. Machen; Narahari Akkaladevi; Caleb Trecazzi; Pierce T. O’Neil; Srayanta Mukherjee; Yifei Qi; Rebecca Dillard; Wonpil Im; Edward P. Gogol; Tommi A. White; Mark T. Fisher

The anthrax lethal toxin consists of protective antigen (PA) and lethal factor (LF). Understanding both the PA pore formation and LF translocation through the PA pore is crucial to mitigating and perhaps preventing anthrax disease. To better understand the interactions of the LF-PA engagement complex, the structure of the LFN-bound PA pore solubilized by a lipid nanodisc was examined using cryo-EM. CryoSPARC was used to rapidly sort particle populations of a heterogeneous sample preparation without imposing symmetry, resulting in a refined 17 Å PA pore structure with 3 LFN bound. At pH 7.5, the contributions from the three unstructured LFN lysine-rich tail regions do not occlude the Phe clamp opening. The open Phe clamp suggests that, in this translocation-compromised pH environment, the lysine-rich tails remain flexible and do not interact with the pore lumen region.

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Yang Zhang

University of Michigan

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Edward P. Gogol

University of Missouri–Kansas City

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Ambrish Roy

University of Michigan

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L. Szerszen

University of Missouri–Kansas City

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