Novel machine learning application for prediction of membrane insertion potential of cell-penetrating peptides

Damiati, Safa A.; Alaofi, Ahmed L.; Dhar, Prajnaparamita; Alhakamy, Nabil A.

doi:10.1016/j.ijpharm.2019.118453

Cited by 17 publications

(14 citation statements)

References 46 publications

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“…Over the last decade, a great attention has been assigned to the importance of CPP on drug transportation of bioactive molecules in various preclinical studies. In fact, novel computational basics have been made in order to develop knowledge on CPPs [39].…”

Section: Optimization Methods For Cpp-mediated Cancer Therapy and Diamentioning

confidence: 99%

Cell-Penetrating Peptides: A Challenge for Drug Delivery

Aroui¹,

Kénani²

2020

Cheminformatics and Its Applications

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Cell-penetrating peptide (CPP) is a term that describes relatively short amphipathic and cationic peptides (7-30 amino acid residues) with rapid translocation across the cell membrane. They can be used to deliver molecular bioactive cargoes due to their efficacy in cellular internalization and also to their low cytotoxicity. In this review we provide an overview of the current approaches and describe the potential of CPP-based drug delivery systems and indicate their powerful promise for clinical efficacy.

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Section: Optimization Methods For Cpp-mediated Cancer Therapy and Diamentioning

confidence: 99%

Cell-Penetrating Peptides: A Challenge for Drug Delivery

Aroui¹,

Kénani²

2020

Cheminformatics and Its Applications

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“…The efficiency of CPPs is usually investigated and screened based on extensive laboratory work, which has recently been successfully performed in silico using ANNs. The developed CPPs/ANN model provided highly accurate predictions and informative assessments for 13 different input features (94). Additionally, drug repurposing also can highly benefit from these technologies (95).…”

Section: Regulatory and Recommendation Insightsmentioning

confidence: 99%

Digital Pharmaceutical Sciences

Damiati

2020

AAPS PharmSciTech

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Artificial intelligence (AI) and machine learning, in particular, have gained significant interest in many fields, including pharmaceutical sciences. The enormous growth of data from several sources, the recent advances in various analytical tools, and the continuous developments in machine learning algorithms have resulted in a rapid increase in new machine learning applications in different areas of pharmaceutical sciences. This review summarizes the past, present, and potential future impacts of machine learning technologies on different areas of pharmaceutical sciences, including drug design and discovery, preformulation, and formulation. The machine learning methods commonly used in pharmaceutical sciences are discussed, with a specific emphasis on artificial neural networks due to their capability to model the nonlinear relationships that are commonly encountered in pharmaceutical research. AI and machine learning technologies in common day-today pharma needs as well as industrial and regulatory insights are reviewed. Beyond traditional potentials of implementing digital technologies using machine learning in the development of more efficient, fast, and economical solutions in pharmaceutical sciences are also discussed.

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“…[ 32 ] The evaluation of seven novel CPP sequences with improved kinetics [ 32 ] further highlights the tremendous potential of such approaches to identify enhanced CPPs and to optimise specific functional parameters such as membrane insertion. [ 33 ] Synthetic molecular evolution (SME), an iterative process employed to design and screen combinatorial libraries exploring the sequence space around known templates, has also been applied to hybrid CPPs. [ 34 ] The screening of a CPP library containing 8192 Tat/penetratin hybrid peptides coupled to an 18‐residue peptide nucleic acid identified gain of function daughter Tat‐ and penetratin‐related sequences.…”

Section: Identification and Sources Of Cpps And Bioportidesmentioning

confidence: 99%

“…The interaction of positively-charged peptides with negatively-charged components of the outer surface of the plasma membrane may be a common first step to promote their internalisation. A fuller appreciation of these processes may also facilitate the computational design and optimisation [32,33] of improved CPP vectors and bioportides. The relative abundance of negatively-charged GAGs, including heparan sulphates, on the cell surface of eukaryotic cells most likely enables a first molecular interaction with some CPPs.…”

Section: Mechanistic Insightsmentioning

confidence: 99%

A new biology of cell penetrating peptides

Howl

Jones

2020

Peptide Science

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As pharmacokinetic modifiers, cell penetrating peptides (CPPs) have proven utility for the delivery of otherwise impermeable cargoes into the discrete intracellular compartments of eukaryotic cells. Methods for the molecular optimisation of CPP sequences can significantly increase the performance of novel vectors matched to a specific delivery function. Moreover, the ‘information rich’ composition and inherent molecular flexibility of many CPPs can also facilitate their interaction with intracellular proteins and other cellular structures. This proteomimetic property of CPPs has been exploited in the design of bioportides, bioactive CPPs that regulate cellular functions often by binding relatively flat PPI interfaces to achieve a dominant negative action. This new biology of CPPs is rapidly gathering momentum through the design and synthesis of a bewildering variety of peptides that may be, in whole or part, linear, helical, cyclic and/or chimeric in nature. A particular emphasis of contemporary CPP‐centred drug discovery is the unmet medical need of cancer, though the biomedical scope of bioportide applications is impressively broad including cellular signalling and reprogramming. We are hopeful that one or more of the fascinating studies described herein will translate into the clinic to establish bioportide technologies as a viable option for drug discovery.

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Novel machine learning application for prediction of membrane insertion potential of cell-penetrating peptides

Cited by 17 publications

References 46 publications

Cell-Penetrating Peptides: A Challenge for Drug Delivery

Cell-Penetrating Peptides: A Challenge for Drug Delivery

Digital Pharmaceutical Sciences

A new biology of cell penetrating peptides

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