Kernel-Elastic Autoencoder for Molecular Design

We introduce the Kernel-Elastic Autoencoder (KAE), a self-supervised generative model based on the transformer architecture with enhanced performance for molecular design. KAE is formulated based on two novel loss functions: modified maximum mean discrepancy and weighted reconstruction. KAE addresses the long-standing challenge of achieving valid generation and accurate reconstruction at the same time. KAE achieves remarkable diversity in molecule generation while maintaining near-perfect reconstructions on the independent testing dataset, surpassing previous molecule-generating models. KAE enables conditional generation and allows for decoding based on beam search resulting in state-of-the-art performance in constrained optimizations. Furthermore, KAE can generate molecules conditional to favorable binding affinities in docking applications as confirmed by AutoDock Vina and Glide scores, outperforming all existing candidates from the training dataset. Beyond molecular design, we anticipate KAE could be applied to solve problems by generation in a wide range of applications

Preserving π-conjugation in covalently functionalized carbon nanotubes for ptoelectronic applications

Covalent functionalization tailors carbon nanotubes for a wide range of applications in varying environments. Its strength and stability of attachment come at the price of degrading the carbon nanotubes sp2 network and destroying the tubes electronic and optoelectronic features. Here we present a non- destructive, covalent, gram-scale functionalization of single-walled carbon nanotubes by a new [2+1] cycloaddition. The reaction rebuilds the extended π-network, thereby retaining the outstanding quantum optoelectronic properties of carbon nanotubes, including bright light emission at high degree of functionalization (1 group per 25 carbon atoms). The conjugation method described here opens the way for advanced tailoring nanotubes as demonstrated for light-triggered reversible doping through photochromic molecular switches and nanoplasmonic gold-nanotube hybrids with enhanced infrared light emission

Identification and mechanistic basis of non-ACE2 blocking neutralizing antibodies from COVID-19 patients with deep RNA sequencing and molecular dynamics simulations

Variants of severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) continue to cause disease and impair the effectiveness of treatments. The therapeutic potential of convergent neutralizing antibodies (NAbs) from fully recovered patients has been explored in several early stages of novel drugs. Here, we identified initially elicited NAbs (Ig Heavy, Ig lambda, Ig kappa) in response to COVID-19 infection in patients admitted to the intensive care unit at a single center with deep RNA sequencing (>100 million reads) of peripheral blood as a diagnostic tool for predicting the severity of the disease and as a means to pinpoint specific compensatory NAb treatments. Clinical data were prospectively collected at multiple time points during ICU admission, and amino acid sequences for the NAb CDR3 segments were identified. Patients who survived severe COVID-19 had significantly more of a Class 3 antibody (C135) to SARS-CoV-2 compared to non-survivors (15059.4 vs. 1412.7, p = 0.016). In addition to highlighting the utility of RNA sequencing in revealing unique NAb profiles in COVID-19 patients with different outcomes, we provided a physical basis for our findings via atomistic modeling combined with molecular dynamics simulations. We established the interactions of the Class 3 NAb C135 with the SARS-CoV-2 spike protein, proposing a mechanistic basis for inhibition via multiple conformations that can effectively prevent ACE2 from binding to the spike protein, despite C135 not directly blocking the ACE2 binding motif. Overall, we demonstrate that deep RNA sequencing combined with structural modeling offers the new potential to identify and understand novel therapeutic(s) NAbs in individuals lacking certain immune responses due to their poor endogenous production. Our results suggest a possible window of opportunity for administration of such NAbs when their full sequence becomes available. A method involving rapid deep RNA sequencing of patients infected with SARS-CoV-2 or its variants at the earliest infection time could help to develop personalized treatments using the identified specific NAbs

Une approche théorique à la photochimie moléculaire basées sur la densité pour l'étude de propriétés remarquables relatives aux états excités moléculaires

This thesis focuses on devising, constructing, and applying cost-effective approaches to calculate the photophysical propertiesof molecular systems in the context of time-dependent density functional theory (TDDFT). The objective of our workis to define a set of purposely-derived density descriptors that can be combined to provide a straightforward interpretationof the relevant photophysical pathways for the many processes taking place at the excited state. More specifically,we deliver a collection of TDDFT-based computational protocols, based on the knowledge of ground and excited statedensities, to characterize the excited-state potential energy surfaces of molecular systems. Overall, the state-trackingalgorithm and the density-descriptors outlined in this thesis collectively provide a reliable and cost-effective way of disclosingexcited state pathways within the theoretical modeling of photophysical processes. The proposed approach canbe computed "on the fly" to identify critical areas for TDDFT approaches while, contextually, providing a method for thequalitative identification - in conjunction with energy criteria - of possible reactions paths.Voire annexe description en englai

Density-based approaches to photo-induced properties and reactivity of molecular systems

Voire annexe description en englaisThis thesis focuses on devising, constructing, and applying cost-effective approaches to calculate the photophysical propertiesof molecular systems in the context of time-dependent density functional theory (TDDFT). The objective of our workis to define a set of purposely-derived density descriptors that can be combined to provide a straightforward interpretationof the relevant photophysical pathways for the many processes taking place at the excited state. More specifically,we deliver a collection of TDDFT-based computational protocols, based on the knowledge of ground and excited statedensities, to characterize the excited-state potential energy surfaces of molecular systems. Overall, the state-trackingalgorithm and the density-descriptors outlined in this thesis collectively provide a reliable and cost-effective way of disclosingexcited state pathways within the theoretical modeling of photophysical processes. The proposed approach canbe computed "on the fly" to identify critical areas for TDDFT approaches while, contextually, providing a method for thequalitative identification - in conjunction with energy criteria - of possible reactions paths

Following excited states in molecular systems using density-based indexes: A dual emissive system as a test case

International audienc

Rationally designed ruthenium complexes for 1- and 2-photon photodynamic therapy

The use of photodynamic therapy (PDT) against cancer has received increasing attention over recent years. However, the application of the currently approved photosensitizers (PSs) is limited by their poor aqueous solubility, aggregation, photobleaching and slow clearance from the body. To overcome these limitations, there is a need for the development of new classes of PSs with ruthenium(II) polypyridine complexes currently gaining momentum. However, these compounds generally lack significant absorption in the biological spectral window, limiting their application to treat deep-seated or large tumors. To overcome this drawback, ruthenium(II) polypyridine complexes designed in silico with (E,E)-4,4 ' -bisstyryl-2,2 ' -bipyridine ligands show impressive 1- and 2-Photon absorption up to a magnitude higher than the ones published so far. While nontoxic in the dark, these compounds are phototoxic in various 2D monolayer cells, 3D multicellular tumor spheroids and are able to eradicate a multiresistant tumor inside a mouse model upon clinically relevant 1-Photon and 2-Photon excitation. p id=Par Photosensitizers that are stable in biological conditions with absorption in the biological spectral window are needed for photodynamic therapy. Here, the authors report on the development of a Ruthenium complex for 1 and 2-photon therapy to address these issues and demonstrate application in vivo

A Ru(II) polypyridyl complex bearing aldehyde functions as a versatile synthetic precursor for long-wavelength absorbing photodynamic therapy photosensitizers

The use of Photodynamic Therapy (PDT) for the treatment of several kinds of cancer as well as bacterial, fungal or viral infections has received increasing attention during the last decade. However, the currently clinically approved photosensitizers (PSs) have several drawbacks, including photobleaching, slow clearance from the organism and poor water solubility. To overcome these shortcomings, many efforts have been made in the development of new types of PSs, such as Ru(II) polypyridyl complexes. Nevertheless, most studied Ru(II) polypyridyl complexes have a low absorbance in the spectral therapeutic window. In this work, we show that, by carefully selecting substituents on the polypyridyl complex, it is possible to prepare a complex absorbing at a much higher wavelength. Specifically, we report on the synthesis as well as in-depth experimental and theoretical characterisation of a Ru(II) polypyridyl complex (complex 3) combining a shift in absorbance towards the spectral therapeutic window with a high 1O2 production. To overcome the absence or poor selectivity of most approved PSs into targeted cells/bacteria, they can be linked to targeting moieties. In this line, compound 3 was designed with reactive aldehyde groups, which can be used as a highly versatile synthetic precursor for further conjugation. As a proof of concept, 3 was reacted with benzylamine and the stability of the resulting conjugate 4 was investigated in DMSO, PBS and cell media. 4 showed an impressive ability to act as a PDT PS with no measurable dark cytotoxicity and photocytotoxicity in the low micromolar range against cancerous HeLa cells from 450 nm up to 540 nm

Chasing unphysical TD-DFT excited states in transition metal complexes with a simple diagnostic tool

International audienceTransition Metal Complexes (TMCs) are known for the rich variety of their excited states showing different nature and degrees of locality. Describing the energies of these excited states with the same degree of accuracy is still problematic when using time-dependent density functional theory in conjunction with the most current density functional approximations. In particular, the presence of unphysically low lying excited states possessing a relevant Charge Transfer (CT) character may significantly affect the spectra computed at such a level of theory and, more relevantly, the interpretation of their photophysical behavior. In this work, we propose an improved version of the MAC index, recently proposed by the authors and collaborators, as a simple and computationally inexpensive diagnostic tool that can be used for the detection and correction of the unphysically predicted low lying excited states. The analysis, performed on five prototype TMCs, shows that spurious and ghost states can appear in a wide spectral range and that it is difficult to detect them only on the basis of their CT extent. Indeed, both delocalization of the excited state and CT extent are criteria that must be combined, as in the MAC index, to detect unphysical states.ACKNOWLEDGME

Chasing unphysical TD-DFT excited states in transition metal complexes with a simple diagnostic tool

International audienceTransition Metal Complexes (TMCs) are known for the rich variety of their excited states showing different nature and degrees of locality. Describing the energies of these excited states with the same degree of accuracy is still problematic when using time-dependent density functional theory in conjunction with the most current density functional approximations. In particular, the presence of unphysically low lying excited states possessing a relevant Charge Transfer (CT) character may significantly affect the spectra computed at such a level of theory and, more relevantly, the interpretation of their photophysical behavior. In this work, we propose an improved version of the MAC index, recently proposed by the authors and collaborators, as a simple and computationally inexpensive diagnostic tool that can be used for the detection and correction of the unphysically predicted low lying excited states. The analysis, performed on five prototype TMCs, shows that spurious and ghost states can appear in a wide spectral range and that it is difficult to detect them only on the basis of their CT extent. Indeed, both delocalization of the excited state and CT extent are criteria that must be combined, as in the MAC index, to detect unphysical states.ACKNOWLEDGME