3 citations · 6 across the 8 of their papers we have counts for
8 papers
Protein Structure-Function Relationship: A Kernel-PCA Approach for Reaction Coordinate Identification
Parisa Mollaei, Amir Barati Farimani
In this study, we propose a Kernel-PCA model designed to capture structure-function relationships in a protein. This model also enables ranking of reaction coordinates according to…
Characterizing the Conformational States of G Protein Coupled Receptors Generated with AlphaFold
Garima Chib, Parisa Mollaei, Amir Barati Farimani
G-Protein Coupled Receptors (GPCRs) are integral to numerous physiological processes and are the target of approximately one-third of FDA-approved therapeutics. Despite their signi…
Multi-Peptide: Multimodality Leveraged Language-Graph Learning of Peptide Properties
Srivathsan Badrinarayanan, Chakradhar Guntuboina, Parisa Mollaei +1
Peptides are essential in biological processes and therapeutics. In this study, we introduce Multi-Peptide, an innovative approach that combines transformer-based language models w…
GradNav: Accelerated Exploration of Potential Energy Surfaces with Gradient-Based Navigation
Janghoon Ock, Parisa Mollaei, Amir Barati Farimani
The exploration of molecular systems' potential energy surface is important for comprehending their complex behaviors, particularly through identifying various metastable states. H…
IDP-Bert: Predicting Properties of Intrinsically Disordered Proteins (IDP) Using Large Language Models
Parisa Mollaei, Danush Sadasivam, Chakradhar Guntuboina +1
Intrinsically Disordered Proteins (IDPs) constitute a large and structure-less class of proteins with significant functions. The existence of IDPs challenges the conventional notio…
Characterization of Phosphorylated Tau-Microtubule complex with Molecular Dynamics (MD) simulation
Seongwon Kim, Parisa Mollaei, Amir Barati Farimani +1
Alzheimer's Disease (AD), a neurodegenerative disorder, is reported as one of the most severe health and socioeconomic problems in current public health. Tau proteins are assumed t…
GPCR-BERT: Interpreting Sequential Design of G Protein Coupled Receptors Using Protein Language Models
Seongwon Kim, Parisa Mollaei, Akshay Antony +2
With the rise of Transformers and Large Language Models (LLMs) in Chemistry and Biology, new avenues for the design and understanding of therapeutics have opened up to the scientif…
PeptideBERT: A Language Model based on Transformers for Peptide Property Prediction
Chakradhar Guntuboina, Adrita Das, Parisa Mollaei +2
Recent advances in Language Models have enabled the protein modeling community with a powerful tool since protein sequences can be represented as text. Specifically, by taking adva…