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While the vast majority of well-structured single protein chains can now be predicted to high accuracy due to the recent AlphaFold [1] model, the prediction of multi-chain protein complexes remains a challenge in many cases. In this work, we demonstrate that an AlphaFold model trained specifically for multimeric inputs of known stoichiometry, which we call AlphaFold-Multimer, significantly increases accuracy of predicted multimeric interfaces over input-adapted single-chain AlphaFold while maintaining high intra-chain accuracy. On a benchmark dataset of 17 heterodimer proteins without templates (introduced in [2]) we achieve at least medium accuracy (DockQ [3]≥0.49) on 14 targets and high accuracy (DockQ≥0.8) on 6 targets, compared to 9 targets of at least medium accuracy and 4 of high accuracy for the previous state of the art system (an AlphaFold-based system from [2]). We also predict structures for a large dataset of 4,433 recent protein complexes, from which we score all non-redundant interfaces with low template identity. For heteromeric interfaces we successfully predict the interface (DockQ≥0.23) in 67% of cases, and produce high accuracy predictions (DockQ≥0.8) in 23% of cases, an improvement of +25 and +11 percentage points over the flexible linker modification of AlphaFold [4] respectively. For homomeric interfaces we successfully predict the interface in 69% of cases, and produce high accuracy predictions in 34% of cases, an improvement of +5 percentage points in both instances.

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We demonstrate that the quantum dot-confined dark exciton forms a long-lived integer spin solid state qubit which can be deterministically on-demand initiated in a pure state by one optical pulse. Moreover, we show that this qubit can be fully controlled using short optical pulses, which are several orders of magnitude shorter than the life and coherence times of the qubit. Our demonstrations do not require an externally applied magnetic field, and they establish that the quantum dotconfined dark exciton forms an excellent solid state matter qubit with some advantages over the half-integer spin qubits, such as the confined electron and hole, separately. Since quantum dots are semiconductor nanostructures that allow integration of electronic and photonic components, the dark exciton may have important implications for implementations of quantum technologies consisting of semiconductor qubits.

We describe the operation and improvement of AlphaFold, the system that was entered by the team AlphaFold2 to the "human" category in the 14th Critical Assessment of Protein Structure Prediction (CASP14). The AlphaFold system entered in CASP14 is entirely different to the one entered in CASP13. It used a novel end-toend deep neural network trained to produce protein structures from amino acid sequence, multiple sequence alignments, and homologous proteins. In the assessors' ranking by summed z scores (>2.0), AlphaFold scored 244.0 compared to 90.8 by the next best group. The predictions made by AlphaFold had a median domain GDT_TS of 92.4; this is the first time that this level of average accuracy has been achieved during CASP, especially on the more difficult Free Modeling targets, and represents a significant improvement in the state of the art in protein structure prediction. We reported how AlphaFold was run as a human team during CASP14 and improved such that it now achieves an equivalent level of performance without intervention, opening the door to highly accurate large-scale structure prediction.

Atomistic tight-binding theory of multiexciton complexes in a selfassembled InAs quantum dot Zieliński, M.; Korkusiński, M.; Hawrylak, P.Contact us / Contactez nous: nparc.cisti@nrc-cnrc.gc.ca. We present atomistic tight-binding theory of electronic structure and optical properties of InAs/GaAs selfassembled quantum dots. The tight-binding model includes zincblende symmetry, faceting, and sp 3 d 5 s ‫ء‬ atomic orbitals accounting for interband and intervalley couplings. The equilibrium positions of atoms are calculated using valence force field method and modification of the tight-binding Hamiltonian due to strain is accounted for using Harrison's law. The electronic and optical properties of multiexciton complexes are then determined by diagonalizing the many-body Hamiltonian for interacting electrons and holes using the configurationinteraction approach. The calculations of strain distribution approach 10 8 atoms while the electron and valence hole single-particle states are calculated by diagonalization of the Hamiltonian matrix with size on the order of 10 7 . The dependence of predicted electronic and optical properties on InAs/GaAs valence-band offset and InAs absolute valence-band deformation potentials are described. The reliability of the atomistic calculations is assessed by comparison with results obtained from the effective bond orbital model and empirical pseudopotentials method.

We use an atomistic model to consider the effect of shape symmetry breaking on the optical properties of self-assembled InAs/GaAs quantum dots. In particular, we investigate the energy level structure and optical activity of the lowest energy excitons in these nanostructures. We compare between quantum dots with two-fold rotational and two reflections (C2v) symmetry and quantum dots in which this symmetry was reduced to one reflection only (Cs) by introducing a facet between the quantum dots and the host material. We show that the symmetry reduction mostly affects the optical activity of the dark exciton. While in symmetric quantum dots, one of the dark exciton eigenstates has a small dipole moment polarized along the symmetry axis (growth direction) of the quantum dot, in non-symmetric ones, the two dark excitons' dipole moments are predominantly cross-linearly polarized perpendicular to the growth direction and reveal pronounced polarization anisotropy. Our model calculations agree quantitatively with recently obtained experimental data.