Abstract: Systems and methods for generating ligand compound structures are provided. A trained computational framework can utilize an initial core ligand compound structure to generate a ligand compound structure by iteratively adding atomic structures. At each iterative step, the computational framework can select a location for adding an atomic structure and can further select which atomic structure is to be added the selected location.

Abstract: Embodiments herein describe systems and methods to predict biomolecule-ligand complexes and uses thereof. Many embodiments generate candidate poses and docking scores for ligands known to interact with a target protein as well as a candidate ligand. Based on similarities present in the candidate poses and docking scores, a pose for the candidate ligand is identified. Many embodiments determine whether a candidate ligand can bind to a target and, if so, determine an affinity. Many embodiments can be used for virtual screening or lead optimization.

Abstract: A computation system for computing interactions in a multiple-body simulation includes an array of processing modules arranged into one or more serially interconnected processing groups of the processing modules. Each of the processing modules includes storage for data elements and includes circuitry for performing pairwise computations between data elements each associated with a spatial location. Each of the pairwise computations makes use of a data element from the storage of the processing module and a data element passing through the serially interconnected processing modules. Each of the processing modules includes circuitry for selecting the pairs of data elements according to separations between spatial locations associated with the data elements.

Abstract: A parallel processing system for computing particle interactions includes a plurality of computation nodes arranged according to a geometric partitioning of a simulation volume. Each computation node has storage for particle data. This particle data is associated with particles in a region of the geometrically partitioned simulation volume. The parallel processing system also includes a communication system having links interconnecting the computation nodes. Each of the computation nodes includes a processor subsystem. These processor subsystems cooperate to coordinate computation of the particle interactions in a distributed manner.

Abstract: A computation system for computing interactions in a multiple-body simulation includes an array of processing modules arranged into one or more serially interconnected processing groups of the processing modules. Each of the processing modules includes storage for data elements and includes circuitry for performing pairwise computations between data elements each associated with a spatial location. Each of the pairwise computations makes use of a data element from the storage of the processing module and a data element passing through the serially interconnected processing modules. Each of the processing modules includes circuitry for selecting the pairs of data elements according to separations between spatial locations associated with the data elements.

Abstract: A generalized approach to particle interaction can confer advantages over previously described method in terms of one or more of communications bandwidth and latency and memory access characteristics. These generalizations can involve one or more of at least spatial decomposition, import region rounding, and multiple zone communication scheduling. An architecture for computation of particle interactions makes use various forms of parallelism. In one implementation, the parallelism involves using multiple computation nodes arranged according to a geometric partitioning of a simulation volume.

Abstract: A computer-implemented method for determining computational units for computing interactions among sets of bodies located in a computation region includes, for each computation associated with one of the sets of bodies, determining, according to an assignment rule that provides a mapping from a location of each of the bodies to a determined computation unit from the plurality of computation units, a computation unit from a plurality of computation units for performing the computation.

Abstract: A generalized approach to particle interaction can confer advantages over previously described method in terms of one or more of communications bandwidth and latency and memory access characteristics. These generalizations can involve one or more of at least spatial decomposition, import region rounding, and multiple zone communication scheduling. An architecture for computation of particle interactions makes use various forms of parallelism. In one implementation, the parallelism involves using multiple computation nodes arranged according to a geometric partitioning of a simulation volume.