Publications

March 2023

Energy for Design : Protein Design using Physics Informed Neural Networks (MDPI bio molecules 2023)

By Sara Ibrahim Omar, Chen Keasar, Ariel J. Ben-Sasson, Eldad Haber.

Abstract
The inverse protein folding problem, also known as protein sequence design, seeks to predict an amino acid sequence that folds into a specific structure and performs a specific function. Recent advancements in machine learning techniques have been successful in generating functional sequences, outperforming previous energy function-based methods. However, these machine learning methods are limited in their interoperability and robustness, especially when designing proteins that must function under non-ambient conditions, such as high temperature, extreme pH, or in various ionic solvents. To address this issue, we propose a new Physics-Informed Neural Networks (PINNs)-based protein sequence design approach. Our approach combines all-atom molecular dynamics simulations, a PINNs MD surrogate model, and a relaxation of binary programming to solve the protein design task while optimizing both energy and the structural stability of proteins. We demonstrate the effectiveness of our design framework in designing proteins that can function under non-ambient conditions.
Keywords: protein design; physics-informed neural networks; binary optimization

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February 2021

Protein backbone design : Mimetic Neural Networks: A unified framework for Protein Design and Folding

Moshe Eliasof, Tue Boesen, Eldad Haber, Chen Keasar, Eran Treister

Recent advancements in machine learning techniques for protein folding motivate better results in its inverse problem — protein design. In this work we introduce a new graph mimetic neural network, MimNet, and show that it is possible to build a reversible architecture that solves the structure and design problems in tandem, allowing to improve protein design when the structure is better estimated. We use the ProteinNet data set and show that the state of the art results in protein design can be improved, given recent architectures for protein folding.

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July 2021

rASA surface estimation : rASA estimation using deep neural networks (ISCB, 2021)

ISCB – INTERNATIONAL SOCIETY FOR COMPUTATIONAL BIOLOGY

Format: Pre-recorded with live Q&A

https://www.iscb.org/cms_addon/conferences/ismbeccb2021/tracks/mlcsb

 

2022

Machine learning for energy calculation

Free energy calculation using deep neural network (Submitted, 2022).

2022

Protein design by convex relaxation

Sparse protein design by convex relaxation (Submitted, 2022).

2013-2023

Dr. Sara Ibrahim Omar’s Body of Work

By Sara Ibrahim Omar

Full List: https://scholar.google.ca/citations?user=poZeicwAAAAJ&hl=en

2021 – Modeling the structure of the frameshift-stimulatory pseudoknot in SARS-CoV-2 reveals multiple possible conformers
Sara Ibrahim Omar, M Zhao, RV Sekar, S Arbabimoghadam, JA Tuszynski, .
Biophysical Journal 120 (3), 313a-314a

2017 – Insights into the Effect of the G245S Single Point Mutation on the Structure of p53 and the Binding of the Protein to DNA
MG Lepre, SI Omar, G Grasso, U Morbiducci, MA Deriu, JA Tuszynski
Molecules

2019 – GLUT1 and TUBB4 in glioblastoma could be efficacious targets
MR Guda, CM Labak, SI Omar, S Asuthkar, S Airala, J Tuszynski,
Cancers 11 (9), 1308

2018 – The molecular mechanism of action of methylene quinuclidinone and its effects on the structure of p53 mutants
Sara Ibrahim Omar, M Zhao, RV Sekar, S Arbabimoghadam, JA Tuszynski, .
Biophysical Journal 120 (3), 313a-314a

2018 – Molecular dynamics and related computational methods with applications to drug discovery
J Preto, F Gentile, P Winter, C Churchill, Sara I. Omar, JA Tuszynski
Coupled Mathematical Models for Physical and Biological Nanoscale Systems

2017 – A computational method for selecting short peptide sequences for inorganic material binding
AL Ravindranath, A Alizadehkhaledi, A Khademi, Sara I. Omar, J Tuszynski,
2018 IEEE 13th Nanotechnology Materials and Devices Conference (NMDC), 1-4

2018 – Characterizing mutant protein activators using single molecule optical trapping
Sara Ibrahim Omar, M Zhao, RV Sekar, S Arbabimoghadam, JA Tuszynski, .
Biophysical Journal 120 (3), 313a-314a

2018 – Protein Structural Analysis of Calbindin D28k Function and Dysregulation: Potential Competition Between Ca2+ and Zn2+
Sara Ibrahim Omar, B C Albensi, K M Gough
Current Alzheimer Research 13 (7), 777-786

2018 – The relative prevalence of the Omicron variant within SARS-CoV-2 infected cohorts in different countries: A systematic review
A Sarkar, Sara Omar, A Alshareef, K Fanous, S Sarker, H Alroobi, F Zamir,
Human Vaccines & Immunotherapeutics 19 (1), 22125684

2018 – Characterizing mutant protein activators using single molecule optical trapping
Sara Ibrahim Omar, M Zhao, RV Sekar, S Arbabimoghadam, JA Tuszynski, .
Biophysical Journal 120 (3), 313a-314a

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