Hit Identification Driven by Combining Artificial Intelligence and Computational Chemistry Methods: A PI5P4K-β Case Study.

Computer-aided drug design (CADD), especially artificial intelligence-driven drug design (AIDD), is increasingly used in drug discovery. In this paper, a novel and efficient workflow for hit identification was developed within the drug discovery platform, featuring innovative artificial intelligence, high-accuracy computational chemistry, and high-performance cloud computing. The workflow was validated by discovering a few potent hit compounds (best IC is ∼0.

New Class of Heterogeneous Helical Peptidomimetics.

A new class of unnatural heterogeneous foldamers is reported to contain alternative α-amino acid and sulfono-γ-AA amino acid residues in a 1:1 repeat pattern. Two-dimensional NMR data show that two 1:1 α/sulfono-γ-AA peptides with diverse side chains form analogous right-handed helical structures in solution. The effects of sequence length, side chain, N-capping, and temperature on folding propensity were further investigated using circular dichroism and small-angle X-ray scattering.

Sulfono-γ-AApeptides as a new class of nonnatural helical foldamer.

Foldamers offer an attractive opportunity for the design of novel molecules that mimic the structures and functions of proteins and enzymes including biocatalysis and biomolecular recognition. Herein we report a new class of nonnatural helical sulfono-γ-AApeptide foldamers of varying lengths. The crystal structure of the sulfono-γ-AApeptide monomer S6 illustrates the intrinsic folding propensity of sulfono-γ-AApeptides, which likely originates from the bulkiness of tertiary sulfonamide moiety.

Design, synthesis and characterization of fMLF-mimicking AApeptides.

The tripeptide N-formyl-Met-Leu-Phe (fMLF) is a potent neutrophil chemoattractant and the reference agonist for the G protein-coupled N-formylpeptide receptor (FPR). As it plays a very important role in host defense and inflammation, there has been considerable interest in the development of fMLF analogues in the hope of identifying potential therapeutic agents. Herein we report the design, synthesis, and evaluation of AApeptides that mimic the structure and function of fMLF.

Synthesis of AApeptides.

The creation and development of nonnatural peptidomimetics has become an area of increasing significance in bioorganic and chemical biology. A wide range of new peptide mimics with novel structures and functions are urgently needed to be explored in order to identify potential drug candidates and targeted probes, and to study protein functions. AApeptides are a new class of peptide mimics based on chiral PNA backbone.

AApeptides as a new class of antimicrobial agents.

Antibiotic resistance is an increasing public health concern around the world, and is recognized as one of the greatest threats facing humankind in the 21(st) century. Natural antimicrobial peptides (AMPs) are small cationic amphiphilic peptides found in virtually all living organisms, and play a key role in the defense against bacterial infections. Compared with conventional antibiotics, which target specific metabolic processes, AMPs are able to adopt globally amphipathic conformations, and kill bacteria through disruption of their membranes.

Lipidated peptidomimetics with improved antimicrobial activity.

We report a series of lipidated α-AApeptides that mimic the structure and function of natural antimicrobial lipopeptides. Several short lipidated α-AApeptides show broad-spectrum activity against a range of clinically related Gram-positive and Gram-negative bacteria as well as fungus. Their antimicrobial activity and selectivity are comparable or even superior to the clinical candidate pexiganan as well as previously reported linear α-AApeptides.

Lipo-γ-AApeptides as a new class of potent and broad-spectrum antimicrobial agents.

There is increasing demand to develop antimicrobial peptides (AMPs) as next generation antibiotic agents, as they have the potential to circumvent emerging drug resistance against conventional antibiotic treatments. Non-natural antimicrobial peptidomimetics are an ideal example of this, as they have significant potency and in vivo stability. Here we report for the first time the design of lipidated γ-AApeptides as antimicrobial agents.

Development of self-immolative dendrimers for drug delivery and sensing.

Traditional dendrimers possess unique cascade-branched structural properties that allow for multivalent modifications with drug cargos, targeting/delivery agents and imaging tools. In addition to multivalency, the dendrimer's macromolecular size also brings about the enhanced permeability and retention (EPR) effect, which makes it an attracting agent for drug delivery and biosensing. Similar to other macromolecules, therapeutic application of dendrimers in the human body faces practical challenges such as target specificity and toxicity.

Development of NGR-based anti-cancer agents for targeted therapeutics and imaging.

Besides the common issue of drug-resistance, the conventional approaches for cancer diagnostics and treatment are constantly challenged by poor selectivity and limited access to neoplastic cells, which not only lead to the dose-limiting effect on the tumor region, but also bring side-effects to healthy cells/tissues. In recent years, a novel strategy has arisen to target the vasculature of tumors for drug-delivery and molecular imaging, based on the success of anti-angiogenic therapy. In addition to being easily accessible, the endothelial cells of tumor vasculature are also genetically stable and thus do not develop drug-resistance, making them ideal targets for chemotherapeutics and biomedical imaging.

Non-hemolytic α-AApeptides as antimicrobial peptidomimetics.

We report a new class of peptide mimetics, α-AApeptides, that display broad-spectrum activity against both Gram-negative and Gram-positive bacteria and fungi. With non-hemolytic activity, resistance to protease hydrolysis, and easy sequence programmability, α-AApeptides may emerge as a novel class of antibiotics.

Design and synthesis of AApeptides: a new class of peptide mimics.

A new family of peptide mimics termed 'AApeptides', which are oligomers of N-acylated-N-aminoethyl amino acids, was proposed. The design and efficient synthesis of AApeptides are described. As proof-of-the-concept, we show that AApeptides can inhibit p53/MDM2 protein-protein interaction with significant activity (IC(50)=38 μM) and specificity.