Self-Activation in De Novo Designed Mimics of Cell-Penetrating Peptides

Abhigyan Som; A. Ozgul Tezgel; Gregory J. Gabriel; Gregory N. Tew

doi:10.1002/ange.201101535

Using molecular dynamics simulations to prioritize and understand AI-generated cell penetrating peptides

Scientific Reports ◽

10.1038/s41598-021-90245-z ◽

2021 ◽

Vol 11 (1) ◽

Author(s):

Duy Phuoc Tran ◽

Seiichi Tada ◽

Akiko Yumoto ◽

Akio Kitao ◽

Yoshihiro Ito ◽

...

Keyword(s):

Molecular Dynamics ◽

De Novo ◽

Homology Modelling ◽

Md Simulations ◽

Cell Penetrating Peptides ◽

Generative Models ◽

Cell Penetrating ◽

Wet Lab ◽

Dynamics Simulations ◽

De Novo Peptide

AbstractCell-penetrating peptides have important therapeutic applications in drug delivery, but the variety of known cell-penetrating peptides is still limited. With a promise to accelerate peptide development, artificial intelligence (AI) techniques including deep generative models are currently in spotlight. Scientists, however, are often overwhelmed by an excessive number of unannotated sequences generated by AI and find it difficult to obtain insights to prioritize them for experimental validation. To avoid this pitfall, we leverage molecular dynamics (MD) simulations to obtain mechanistic information to prioritize and understand AI-generated peptides. A mechanistic score of permeability is computed from five steered MD simulations starting from different initial structures predicted by homology modelling. To compensate for variability of predicted structures, the score is computed with sample variance penalization so that a peptide with consistent behaviour is highly evaluated. Our computational pipeline involving deep learning, homology modelling, MD simulations and synthesizability assessment generated 24 novel peptide sequences. The top-scoring peptide showed a consistent pattern of conformational change in all simulations regardless of initial structures. As a result of wet-lab-experiments, our peptide showed better permeability and weaker toxicity in comparison to a clinically used peptide, TAT. Our result demonstrates how MD simulations can support de novo peptide design by providing mechanistic information supplementing statistical inference.

Cell-Penetrating Peptides Derived from Animal Venoms and Toxins

Toxins ◽

10.3390/toxins13020147 ◽

2021 ◽

Vol 13 (2) ◽

pp. 147

Author(s):

Gandhi Rádis-Baptista

Keyword(s):

Plasma Membranes ◽

Cytoplasmic Membrane ◽

De Novo ◽

Cell Types ◽

Cell Penetrating Peptides ◽

Cumulative Number ◽

Cell Cytoplasm ◽

Cell Penetrating ◽

Animal Venoms ◽

Pharmaceutical Biotechnology

Cell-penetrating peptides (CPPs) comprise a class of short polypeptides that possess the ability to selectively interact with the cytoplasmic membrane of certain cell types, translocate across plasma membranes and accumulate in the cell cytoplasm, organelles (e.g., the nucleus and mitochondria) and other subcellular compartments. CPPs are either of natural origin or de novo designed and synthesized from segments and patches of larger proteins or designed by algorithms. With such intrinsic properties, along with membrane permeation, translocation and cellular uptake properties, CPPs can intracellularly convey diverse substances and nanomaterials, such as hydrophilic organic compounds and drugs, macromolecules (nucleic acids and proteins), nanoparticles (nanocrystals and polyplexes), metals and radionuclides, which can be covalently attached via CPP N- and C-terminals or through preparation of CPP complexes. A cumulative number of studies on animal toxins, primarily isolated from the venom of arthropods and snakes, have revealed the cell-penetrating activities of venom peptides and toxins, which can be harnessed for application in biomedicine and pharmaceutical biotechnology. In this review, I aimed to collate examples of peptides from animal venoms and toxic secretions that possess the ability to penetrate diverse types of cells. These venom CPPs have been chemically or structurally modified to enhance cell selectivity, bioavailability and a range of target applications. Herein, examples are listed and discussed, including cysteine-stabilized and linear, α-helical peptides, with cationic and amphipathic character, from the venom of insects (e.g., melittin, anoplin, mastoparans), arachnids (latarcin, lycosin, chlorotoxin, maurocalcine/imperatoxin homologs and wasabi receptor toxin), fish (pardaxins), amphibian (bombesin) and snakes (crotamine and cathelicidins).