Juan Perilla

Assistant Professor | University of Delaware

Newark, DE, UNITED STATES

Juan Perilla develops physical and chemical based methodologies for the understanding of biological process related to life and disease

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Biography

Dr. Perilla is a biophysical chemist, currently an Assistant Professor of Chemistry & Biochemistry at the University of Delaware.

He obtained his Ph.D. in 2011 at Johns Hopkins University, researching transition state theory applied to large conformational changes in proteins. He then moved to the University of Illinois at Urbana-Champaign (Prof. Klaus Schulten's group), where he studied entire viruses and bacterial organelles under physiological conditions.

Prof. Perilla develops physical and chemical based methodologies for the understanding of biological process related to life and disease. In particular, his research spans from quantum-mechanical calculations to mesoscale simulations and leverages the computational power of petascale and exascale super computers.

Prof. Perilla has conducted the largest simulations ever performed,which allowed him to develop a robust statistical analysis framework for such big datasets. He has authored ~50 peer-reviewed articles, 11 journal covers and three book chapters.

Dr. Perilla enjoys sports like squash, golf, long-distance road cycling, as well as playing chess and the violin.

Areas of Expertise (6)

Computational Physics

Computational Chemistry

Data Science

Machine Learning

Molecular Virology

Biophysics

Articles (3)

The Drug-Induced Interface That Drives HIV-1 Integrase Hypermultimerization and Loss of Function

Mbio

2023 Allosteric HIV-1 integrase (IN) inhibitors (ALLINIs) are an emerging class of small molecules that disrupt viral maturation by inducing the aberrant multimerization of IN. Here, we present cocrystal structures of HIV-1 IN with two potent ALLINIs, namely, BI-D and the drug candidate Pirmitegravir. The structures reveal atomistic details of the ALLINI-induced interface between the HIV-1 IN catalytic core and carboxyl-terminal domains (CCD and CTD). Projecting from their principal binding pocket on the IN CCD dimer, the compounds act as molecular glue by engaging a triad of invariant HIV-1 IN CTD residues, namely, Tyr226, Trp235, and Lys266, to nucleate the CTD-CCD interaction. The drug-induced interface involves the CTD SH3-like fold and extends to the beginning of the IN carboxyl-terminal tail region. We show that mutations of HIV-1 IN CTD residues that participate in the interface with the CCD greatly reduce the IN-aggregation properties of Pirmitegravir. Our results explain the mechanism of the ALLINI-induced condensation of HIV-1 IN and provide a reliable template for the rational development of this series of antiretrovirals through the optimization of their key contacts with the viral target.

Performance efficient macromolecular mechanics via sub-nanometer shape based coarse graining Authors Alexander J Bryer, Juan R Perilla

bioRxiv

2022 Dimensionality reduction via coarse grain modeling has positioned itself as an indispensable tool for decades, particularly for biomolecular simulations where atomic systems encompass hundreds of millions of atoms. While distinct flavors of coarse grain modeling exist, those occupying the coarse end of the spectrum are typically knowledge based, relying on a priori information to parameterize models, thus hindering general predictive capability. Here, we present an algorithmic and transferable approach known as shape based coarse graining (SBCG) which employs unsupervised machine learning via competitive Hebbian adaptation to construct coarse molecules that perfectly represent atomistic topologies. We show how SBCG provides ample control over model granularity, and we provide a quantitative metric for selection thereof. Parameter optimization, inclusion of small molecule species, as well as simulation configuration are discussed in detail. Our method and its implementation is made available as part of the CGBuilder plugin, present in the widely-used visual molecular dynamics (VMD) and nanoscale molecular dynamics (NAMD) software suites. We demonstrate applications of our method with a variety of systems from the inositol hexaphosphate-bound, full-scale HIV-1 capsid to heteromultimeric cofilin-2-bound actin filaments.

Recognition of the TDP-43 nuclear localization signal by importin α1/β

Cell Reports

2022 Cytoplasmic mislocalization of the TAR-DNA binding protein of 43 kDa (TDP-43) leads to large, insoluble aggregates that are a hallmark of amyotrophic lateral sclerosis and frontotemporal dementia. Here, we study how importin α1/β recognizes TDP-43 bipartite nuclear localization signal (NLS). We find that the NLS makes extensive contacts with importin α1, especially at the minor NLS-binding site. NLS binding results in steric clashes with the C terminus of importin α1 that disrupts the TDP-43 N-terminal domain (NTD) dimerization interface. A putative phosphorylation site in the proximity of TDP-43 R83 at the minor NLS site destabilizes binding to importins by reducing the NLS backbone dynamics. Based on these data, we explain the pathogenic role of several post-translational modifications and mutations in the proximity of TDP-43 minor NLS site that are linked to disease and shed light on the chaperone activity of importin α1/β.