A series of pH and GSH responsive photosensitizers were designed and synthesized. pK a values were optimized by adjusting the inductive contribution of substituents to reach a pH range (6.0-7.4) relevant to the tumour microenvironment. pH-Activatable behaviour and redox mediated release of the quencher from the PS by GSH allow the construction of an AND logic operator for selective photodynamic action in aqueous solutions.The research in molecular logic gates, which was initiated by the seminal work by de Silva, 1 blossomed in the two decades that followed. 2 In addition, the limitations and the potential of this approach has become more clear. A particularly promising application of molecular logic gates may be in the field of information processing therapeutic agents. Incorporation of Boolean logic ideas in the function of therapeutic agents would be very valuable, if the same results cannot be achieved by random optimization studies. Previously, our group and others provided the early examples of the work in that direction. 3 Our first proof of principle work which linked photodynamic sensitization of a Bodipy based photosensitizer (PS) to the concentrations of sodium ions and the acidity was essentially an AND logic gate, but the system required organic solvents and organic acid to function in the desired manner. While it was considered to be noteworthy for that approach to have practical potential, an AND logic gate based enhanced selectivity should be related to cancer related biological parameters, which can generate significant changes in the photophysical character of the sensitizer in aqueous solutions.In this work, we took advantage of two characteristics of the tumour microenvironment, lower pH and higher glutathione concentrations. 4 The difference in pH between cancer tissue and healthy tissue is an easily accessible parameter for use in therapeutic activation. A number of pH-responsive polymeric materials, photosensitizers, and nanocarriers were studied to control drug release or activation. 5 However, extracellular pH of tumor cells drops to a value not below 6.0. 6 Thus, it is challenging to find a smart therapeutic system responsive to pH within the narrow near neutral range and essentially become active at around pH 6.0-6.5 and stay inactive above pH 7.0. Apart from some, 7 most related studies in the literature depend on activation at pH below 5.5, which actually requires nonselective lysosomal activation. 8 In this work, the properties of the PS are optimized for pH activatability by causing rational chemical modification on the pH responsive moiety with electron donating or withdrawing groups to adjust the pK a to the desired near-neutral value and to get enough spectral shift in acidic aqueous solutions such that protonated PSs are exclusively excited species under the conditions of interest. Thus, the overall design (Scheme 1) involves a pH responsive unit, linked to a quencher, which could be cleaved at elevated GSH concentrations. Previously, GSH has been used as a PS activator mostly t...

Systematic cascading of molecular logic gates is an important issue to be addressed for advancing research in this field. We have demonstrated that photochemically triggered metal ion signals can be utilized towards that goal. Thus, independent logic gates were shown to work together while keeping their identity in more complex logic designs. Communication through the intermediacy of ion signals is clearly inspired from biological processes modulated by such signals, and implemented here with ion responsive molecules.

A ligand incorporating a dithioethenyl moiety is cleaved into fragments which have a lower metal-ion affinity upon irradiation with low-energy red/near-IR light. The cleavage is a result of singlet oxygen generation which occurs on excitation of the photosensitizer modules. The method has many tunable factors that could make it a satisfactory caging strategy for metal ions.

A two-dimensional nanoparticle–single-stranded DNA (ssDNA) array has been assembled for the detection of bacterial species using machine-learning (ML) algorithms. Out of 60 unknowns prepared from bacterial lysates, 54 unknowns were predicted correctly. Furthermore, the nanosensor array, supported by ML algorithms, was able to distinguish wild-type Escherichia coli from its mutant by a single gene difference. In addition, the nanosensor array was able to distinguish untreated wild-type E. coli from those treated with antimicrobial drugs. This work demonstrates the potential of nanoparticle–ssDNA arrays and ML algorithms for the discrimination and identification of complex biological matrixes.