Automatic pedicle screw planning using atlas-based registration of anatomy and reference trajectories

An algorithm for automatic spinal pedicle screw planning is reported and evaluated in simulation and first clinical studies. A statistical atlas of the lumbar spine (N  =  40 members) was constructed for active shape model (ASM) registration of target vertebrae to an unsegmented patient CT. The atlas was augmented to include 'reference' trajectories through the pedicles as defined by a spinal neurosurgeon. Following ASM registration, the trajectories are transformed to the patient CT and accumulated to define a patient-specific screw trajectory, diameter, and length. The algorithm was evaluated in leave-one-out analysis (N  =  40 members) and for the first time in a clinical study (N  =  5 patients undergoing cone-beam CT (CBCT) guided spine surgery), and in simulated low-dose CBCT images. ASM registration achieved (2.0  ±  0.5) mm root-mean-square-error (RMSE) in surface registration in 96% of cases, with outliers owing to limitations in CT image quality (high noise/slice thickness). Trajectory centerlines were conformant to the pedicle in 95% of cases. For all non-breaching trajectories, automatically defined screw diameter and length were similarly conformant to the pedicle and vertebral body (98.7%, Grade A/B). The algorithm performed similarly in CBCT clinical studies (93% centerline and screw conformance) and was consistent at the lowest dose levels tested. Average runtime in planning five-level (lumbar) bilateral screws (ten trajectories) was (312.1  ±  104.0) s. The runtime per level for ASM registration was (41.2  ±  39.9) s, and the runtime per trajectory was (4.1  ±  0.8) s, suggesting a runtime of ~(45.3  ±  39.9) s with a more fully parallelized implementation. The algorithm demonstrated accurate, automatic definition of pedicle screw trajectories, diameter, and length in CT images of the spine without segmentation. The studies support translation to clinical studies in free-hand or robot-assisted spine surgery, quality assurance, and data analytics in which fast trajectory definition is a benefit to workflow.

DeepSite: protein-binding site predictor using 3D-convolutional neural networks

Motivation

An important step in structure-based drug design consists in the prediction of druggable binding sites. Several algorithms for detecting binding cavities, those likely to bind to a small drug compound, have been developed over the years by clever exploitation of geometric, chemical and evolutionary features of the protein.

Results

Here we present a novel knowledge-based approach that uses state-of-the-art convolutional neural networks, where the algorithm is learned by examples. In total, 7622 proteins from the scPDB database of binding sites have been evaluated using both a distance and a volumetric overlap approach. Our machine-learning based method demonstrates superior performance to two other competitive algorithmic strategies.

Availability and implementation

DeepSite is freely available at www.playmolecule.org. Users can submit either a PDB ID or PDB file for pocket detection to our NVIDIA GPU-equipped servers through a WebGL graphical interface.

Contact

gianni.defabritiis@upf.edu.

Supplementary information

Supplementary data are available at Bioinformatics online.

HTMD: High-Throughput Molecular Dynamics for Molecular Discovery

Recent advances in molecular simulations have allowed scientists to investigate slower biological processes than ever before. Together with these advances came an explosion of data that has transformed a traditionally computing-bound into a data-bound problem. Here, we present HTMD, a programmable, extensible platform written in Python that aims to solve the data generation and analysis problem as well as increase reproducibility by providing a complete workspace for simulation-based discovery. So far, HTMD includes system building for CHARMM and AMBER force fields, projection methods, clustering, molecular simulation production, adaptive sampling, an Amazon cloud interface, Markov state models, and visualization. As a result, a single, short HTMD script can lead from a PDB structure to useful quantities such as relaxation time scales, equilibrium populations, metastable conformations, and kinetic rates. In this paper, we focus on the adaptive sampling and Markov state modeling features.

Kinetic characterization of fragment binding in AmpC β-lactamase by high-throughput molecular simulations

Small molecules used in fragment-based drug discovery form multiple, promiscuous binding complexes difficult to capture experimentally. Here, we identify such binding poses and their associated energetics and kinetics using molecular dynamics simulations on AmpC β-lactamase. Only one of the crystallographic binding poses was found to be thermodynamically favorable; however, the ligand shows several binding poses within the pocket. This study demonstrates free-binding molecular simulations in the context of fragment-to-lead development and its potential application in drug design.

Comparison between chromatin condensation and morphology from testis biopsy extracted and ejaculated spermatozoa and their relationship to ICSI outcome

A significant association between male subfertility, imperfect spermiation and abnormal nuclear condensation has been suggested. The DNA content of spermatozoa might be responsible for inducing alterations in sperm morphology. The final nuclear shape, which is species-specific, depends on chromatin condensation during spermatogenesis as well as a precise organization of DNA within the nucleus. Many reports have described the association between disturbances in sperm chromatin condensation, morphology and male infertility. Chromatin condensation is achieved by gradual substitution of lysinerich somatic histones by testis-specific histone and finally by protamine. In this study two groups of patients were compared: the first consisted of 63 patients who had undergone intracytoplasmic sperm injection (ICSI) with freshly ejaculated spermatozoa whereas the second included 47 patients assigned to ICSI with testes biopsy-extracted spermatozoa. In both groups chromatin condensation was assessed by aniline blue staining and morphology evaluated according to strict criteria. The condensed chromatin and morphology of spermatozoa were significantly (P < 0.0001) less in the second group compared to the first. However the fertilization, cleavage, implantation and pregnancy rates were almost the same in both investigated groups. There was no significant difference between the two groups with respect to ICSI outcome. The percentage of chromatin condensation (nuclear maturity) and morphologically-normal spermatozoa were significantly higher (P < 0.0001) in the ejaculated spermatozoa than in those from testis biopsy but the ICSI outcome (fertilization, cleavage, implantation and pregnancy rates) was the same. In view of these results the fertilization capability and the embryo quality obtained using testis biopsy extracted spermatozoa is not influenced by chromatin condensation and sperm morphology in testicular sperm extraction (TESE)-ICSI programmes. Therefore, it could be said that neither chromatin condensation nor morphology of testis extracted sperm could predict the fertilization, implantation and pregnancy rate in TESE-ICSI programmes.