Publications by authors named "Arash Firouzbakht"

Hirudin is a bioactive small protein that binds thrombin to interrupt the blood clotting cascade. It contains an ordered and a disordered (IDR) region. Conjugating with polyethylene glycol (PEGylation) is an important modification of biopharmaceuticals to improve their lifetime and retention.

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Intrinsically disordered proteins (IDPs) that lie close to the empirical boundary separating IDPs and folded proteins in Uversky's charge-hydropathy plot may behave as "marginal IDPs" and sensitively switch conformation upon changes in environment (temperature, crowding, and charge screening), sequence, or both. In our search for such a marginal IDP, we selected Huntingtin-interacting protein K (HYPK) near that boundary as a candidate; PKIα, also near that boundary, has lower secondary structure propensity; and Crk1, just across the boundary on the folded side, has higher secondary structure propensity. We used a qualitative Förster resonance energy transfer-based assay together with circular dichroism to simultaneously probe global and local conformation.

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Translocation of proteins is correlated with structural fluctuations that access conformational states higher in free energy than the folded state. We use electric fields at the solid-state nanopore to control the relative free energy and occupancy of different protein conformational states at the single-molecule level. The change in occupancy of different protein conformations as a function of electric field gives rise to shifts in the measured distributions of ionic current blockades and residence times.

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Conformational transitions of proteins are governed by chemical kinetics, often toggled by passage through an activated state separating two conformational ensembles. The passage time of a protein through the activated state can be too fast to be detected by single-molecule experiments without the aid of viscogenic agents. Here, we use high-bandwidth nanopore measurements to resolve microsecond-duration transitions that occur between conformational states of individual protein molecules partly blocking pore current.

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Deep learning's automatic feature extraction has been a revolutionary addition to computational drug discovery, infusing both the capabilities of learning abstract features and discovering complex molecular patterns via learning from molecular data. Since biological and chemical knowledge are necessary for overcoming the challenges of data curation, balancing, training, and evaluation, it is important for databases to contain information regarding the exact target and disease of each bioassay. The existing depositories such as PubChem or ChEMBL offer the screening data for millions of molecules against a variety of cells and targets, however, their bioassays contain complex biological descriptions which can hinder their usage by the machine learning community.

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Lasso peptides are a class of ribosomally synthesized and post-translationally modified natural product which possess a unique lariat knot conformation. The low entropy "threaded" conformation endows lasso peptides with considerable resistance to heat and proteolytic degradation, which are attractive properties for the development of peptide-based therapeutics. Despite their discovery nearly 30 years ago, the molecular mechanism underlying lasso peptide biosynthesis remains poorly characterized due to the low stability of the purified biosynthetic enzymes.

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