Sutanu Bhattacharya

Sutanu Bhattacharya
Florida Polytechnic University · Computer Science

Doctor of Philosophy

About

18
Publications
731
Reads
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41
Citations
Introduction
My basic interest lies in template-based protein 3D structure prediction, particularly information guided protein threading for weakly homologous proteins.
Additional affiliations
July 2017 - March 2020
Auburn University
Position
  • Research Assistant
Description
  • I am working on template based protein 3D structure prediction, more specifically I am dealing with protein threading.
July 2014 - August 2017
Kolhan University
Position
  • Lecturer
Description
  • I worked at Chaibasa Engineering College, India.
Education
August 2017 - December 2021
Auburn University
Field of study
  • Computer Science and Software Engineering

Publications

Publications (18)
Article
Protein contact maps have proven to be a valuable tool in the deep learning revolution of protein structure prediction, ushering in the recent breakthrough by AlphaFold2. However, self‐assessment of the quality of predicted structures are typically performed at the granularity of 3D coordinates as opposed to directly exploiting the rotation‐ and tr...
Preprint
Motivation Protein contact maps have proven to be a valuable tool in the deep learning revolution of protein structure prediction, ushering in the recent breakthrough by AlphaFold2. However, self-assessment of the quality of predicted structures is typically performed at the granularity of 3D coordinates as opposed to directly exploiting the rotati...
Article
Threading a query protein sequence onto a library of weakly homologous structural templates remains challenging, even when sequence-based predicted contact or distance information is used. Contact- or distance-assisted threading methods utilize only the spatial proximity of the interacting residue pairs for template selection and alignment, ignorin...
Article
Full-text available
Sequence-based protein homology detection has emerged as one of the most sensitive and accurate approaches to protein structure prediction. Despite the success, homology detection remains very challenging for weakly homologous proteins with divergent evolutionary profile. Very recently, deep neural network architectures have shown promising progres...
Article
Full-text available
Crystallography and NMR system (CNS) is currently a widely used method for fragment-free ab initio protein folding from inter-residue distance or contact maps. Despite its widespread use in protein structure prediction, CNS is a decade-old macromolecular structure determination system that was originally developed for solving macromolecular geometr...
Article
Full-text available
Recent advances in distance-based protein folding have led to a paradigm shift in protein structure prediction. Through sufficiently precise estimation of the inter-residue distance matrix for a protein sequence, it is now feasible to predict the correct folds for new proteins much more accurately than ever before. Despite the exciting progress, a...
Preprint
Crystallography and NMR system (CNS) is currently the de facto standard for fragment-free ab initio protein folding from inter-residue distance or contact maps. Despite its widespread use in protein structure prediction, CNS is a decade-old macromolecular structure determination system that was originally developed for solving macromolecular geomet...
Article
Full-text available
Motivation: Protein model quality estimation, in many ways, informs protein structure prediction. Despite their tight coupling, existing model quality estimation methods do not leverage inter-residue distance information or the latest technological breakthrough in deep learning that has recently revolutionized protein structure prediction. Result...
Article
Full-text available
The development of improved threading algorithms for remote homology modeling is a critical step forward in template-based protein structure prediction. We have recently demonstrated the utility of contact information to boost protein threading by developing a new contact-assisted threading method. However, the nature and extent to which the qualit...
Preprint
Recent advances in distance-based protein folding have led to a paradigm shift in protein structure prediction. Through sufficiently precise estimation of the inter-residue distance matrix for a protein sequence, it is now feasible to predict the correct folds for new proteins much more accurately than ever before. Despite the exciting progress, a...
Preprint
Motivation Protein model quality estimation, in many ways, informs protein structure prediction. Despite their tight coupling, existing model quality estimation methods do not leverage inter-residue distance information or the latest technological breakthrough in deep learning that has recently revolutionized protein structure prediction. Results...
Preprint
Motivation Threading a query protein sequence onto a library of weakly homologous structural templates remains challenging, even when sequence-based predicted contact or distance information is used. Contact- or distance-assisted threading methods utilize only the spatial proximity of the interacting residue pairs for template selection and alignme...
Conference Paper
Protein threading is a powerful approach for predicting protein three-dimensional structure particularly when direct homologous relationships with known structures cannot be easily detected. However, remote homology detection via threading remains challenging, in part, due to the limitations of threading scoring function for selecting optimal struc...
Conference Paper
Protein threading is a popular template-based approach for predicting protein three-dimensional structure in the absence of close templates. However, identifying remote homologous templates remains challenging. Inspired by recent progress in inter-residue contact prediction driven by sequence co-evolution and deep learning, we have developed a new...
Article
Obverse Cover: The cover image is based on the Research Article Does inclusion of residue‐residue contact information boost protein threading? by Sutanu Bhattacharya, Debswapna Bhattacharya, DOI 10.1002/prot.25684.
Article
Full-text available
Template‐based modeling is considered as one of the most successful approaches for protein structure prediction. However, reliably and accurately selecting optimal template proteins from a library of known protein structures having similar folds as the target protein and making correct alignments between the target sequence and the template structu...

Projects

Projects (2)
Project
Prediction of quality of single protein structural models by leveraging deep learning architecture
Project
Threading methods which successfully fold proteins, having distant evolutionary relationship with known protein 3D structures or templates.