Non-invasive approaches to functional recovery after spinal cord injury: Therapeutic targets and multimodal device interventions.

This paper is an interdisciplinary narrative review of efficacious non-invasive therapies that are increasingly used to restore function in people with chronic spinal cord injuries (SCI). First presented are the secondary injury cascade set in motion by the primary lesion and highlights in therapeutic development for mitigating the acute pathophysiologic process. Then summarized are current pharmacological strategies for modulation of noradrenergic, serotonergic, and dopaminergic neurotransmission to enhance recovery in bench and clinical studies of subacute and chronic SCI. Last examined is how neuromechanical devices (i.e., electrical stimulation, robotic assistance, brain-computer interface, and augmented sensory feedback) could be comprehensively engineered to engage efferent and afferent motosensory pathways to induce neuroplasticity-based neural pattern generation. Emerging evidence shows that computational models of the human neuromusculoskeletal system (i.e., human digital twins) can serve as functionalized anchors to integrate different neuromechanical and pharmacological interventions into a single multimodal prothesis. The system, if appropriately built, may cybernetically optimize treatment outcomes via coordination of heterogeneous biosensory, system output, and control signals. Overall, these rehabilitation protocols involved neuromodulation to evoke beneficial adaptive changes within spared supraspinal, intracord, and peripheral neuromuscular circuits to elicit neurological improvement. Therefore, qualitatively advancing the theoretical understanding of spinal cord neurobiology and neuromechanics is pivotal to designing new ways to reinstate locomotion after SCI. Future research efforts should concentrate on personalizing combination therapies consisting of pharmacological adjuncts, targeted neurobiological and neuromuscular repairs, and brain-computer interfaces, which follow multimodal neuromechanical principles.

Optimisation of estrogen receptor subtype-selectivity of a 4-Aryl-4H-chromene scaffold previously identified by virtual screening.

4-Aryl-4H-Chromene derivatives have been previously shown to exhibit anti-proliferative, apoptotic and anti-angiogenic activity in a variety of tumor models in vitro and in vivo generally via activation of caspases through inhibition of tubulin polymerisation. We have previously identified by Virtual Screening (VS) a 4-aryl-4H-chromene scaffold, of which two examples were shown to bind Estrogen Receptor α and ß with low nanomolar affinity and <20-fold selectivity for α over ß and low micromolar anti-proliferative activity in the MCF-7 cell line. Thus, using the 4-aryl-4H-chromene scaffold as a starting point, a series of compounds with a range of basic arylethers at C-4 and modifications at the C3-ester substituent of the benzopyran ring were synthesised, producing some potent ER antagonists in the MCF-7 cell line which were highly selective for ERα (compound 35; 350-fold selectivity) or ERß (compound 42; 170-fold selectivity).

Biofeedback for Gait Retraining Based on Real-Time Estimation of Tibiofemoral Joint Contact Forces.

Biofeedback assisted rehabilitation and intervention technologies have the potential to modify clinically relevant biomechanics. Gait retraining has been used to reduce the knee adduction moment, a surrogate of medial tibiofemoral joint loading often used in knee osteoarthritis research. In this paper, we present an electromyogram-driven neuromusculoskeletal model of the lower-limb to estimate, in real-time, the tibiofemoral joint loads. The model included 34 musculotendon units spanning the hip, knee, and ankle joints. Full-body inverse kinematics, inverse dynamics, and musculotendon kinematics were solved in real-time from motion capture and force plate data to estimate the knee medial tibiofemoral contact force (MTFF). We analyzed five healthy subjects while they were walking on an instrumented treadmill with visual biofeedback of their MTFF. Each subject was asked to modify their gait in order to vary the magnitude of their MTFF. All subjects were able to increase their MTFF, whereas only three subjects could decrease it, and only after receiving verbal suggestions about possible gait modification strategies. Results indicate the important role of knee muscle activation patterns in modulating the MTFF. While this paper focused on the knee, the technology can be extended to examine the musculoskeletal tissue loads at different sites of the human body.

"True" antiandrogens-selective non-ligand-binding pocket disruptors of androgen receptor-coactivator interactions: novel tools for prostate cancer.

Prostate cancer (PCa) therapy typically involves administration of "classical" antiandrogens, competitive inhibitors of androgen receptor (AR) ligands, dihydrotestosterone (DHT) and testosterone (tes), for the ligand-binding pocket (LBP) in the ligand-binding domain (LBD) of AR. Prolonged LBP-targeting leads to resistance, and alternative therapies are urgently required. We report the identification and characterization of a novel series of diarylhydrazides as selective disruptors of AR interaction with coactivators through application of structure and ligand-based virtual screening. Compounds demonstrate full ("true") antagonism in AR with low micromolar potency, selectivity over estrogen receptors α and ß and glucocorticoid receptor, and partial antagonism of the progesterone receptor. MDG506 (5) demonstrates low cellular toxicity in PCa models and dose responsive reduction of classical antiandrogen-induced prostate specific antigen expression. These data provide compelling evidence for such non-LBP intervention as an alternative approach or in combination with classical PCa therapy.

Screening for inhibitors of tau protein aggregation into Alzheimer paired helical filaments: a ligand based approach results in successful scaffold hopping.

The aggregation of tau protein into paired helical filaments is one of the hallmarks of Alzheimer's disease and related dementias. We therefore continue our search for non-toxic, cell penetrating inhibitors of tau aggregation, which hold potential for brain penetration. Pickhardt et al. (2005) have reported a high throughput screen for tau aggregation inhibitors previously, which resulted in the identification of several hit classes. Here we report the identification of novel inhibitors which were not present in the initial high throughput assay. This was achieved by transformation of the high throughput screen data into the 3D relationships of virtual pharmacophores The pharmacophore models were utilized in a virtual screen of a Maybridge database. The virtual screen provided 136 hits; 19 representative hits were selected and assayed, this resulted in two novel leads with an IC(50) < 13 microM. These two leads feature a novel scaffold for tau aggregation inhibitors.

Permuting input for more effective sampling of 3D conformer space.

SMILES strings and other classic 2D structural formats offer a convenient way to represent molecules as a simplistic connection table, with the inherent advantages of ease of handling and storage. In the context of virtual screening, chemical databases to be screened are often initially represented by canonicalised SMILES strings that can be filtered and pre-processed in a number of ways, resulting in molecules that occupy similar regions of chemical space to active compounds of a therapeutic target. A wide variety of software exists to convert molecules into SMILES format, namely, Mol2smi (Daylight Inc.), MOE (Chemical Computing Group) and Babel (Openeye Scientific Software). Depending on the algorithm employed, the atoms of a SMILES string defining a molecule can be ordered differently. Upon conversion to 3D coordinates they result in the production of ostensibly the same molecule. In this work we show how different permutations of a SMILES string can affect conformer generation, affecting reliability and repeatability of the results. Furthermore, we propose a novel procedure for the generation of conformers, taking advantage of the permutation of the input strings--both SMILES and other 2D formats, leading to more effective sampling of conformation space in output, and also implementing fingerprint and principal component analyses step to post process and visualise the results.

Estrogen receptors: molecular interactions, virtual screening and future prospects.

Identification of the Estrogen Receptor (ER) as a key mediator of the proliferation of breast cancer, and its involvement in pathways leading to osteoporosis and coronary heart disease, has resulted in a surge to discover and design compounds with the ability to modulate its actions (SERMs). Concurrently, a dramatic increase in the number of crystal structures of the ER has led to a more in depth understanding of the governing mechanisms involved in ER modulation. Entwining computational techniques with the availability of 3D structural data, has allowed not only the rational design of potent inhibitors of the ER, but also its incorporation in Virtual Screening (VS) in the search for novel chemotypes that can modulate the ER. An important initial step in the VS process is to filter towards molecules that occupy similar chemical space to a set of known actives prior to docking. We illustrate through Principal Component Analysis (PCA) of 145 descriptors the region of chemical space antiestrogens occupy compared with 'drug-like' space. We also review all available studies involving validation of several docking algorithms utilizing the ER, ultimately focusing on analysis of Enrichment (E) rates and False Positive (FP) rates to illustrate the successes attributed to each docking algorithm. Finally, we relate the recent discovery of non-genomic mechanisms of the ER and subsequently present a model involving a recently identified alternative, second binding-pocket of the ER in our laboratory through cavity analysis that suggests how the same receptor can invoke these, 'classical' and rapid responses concurrently.

Considerations in compound database preparation--"hidden" impact on virtual screening results.

Structure-based virtual screening (SBVS) utilizing docking algorithms has become an essential tool in the drug discovery process, and significant progress has been made in successfully applying the technique to a wide range of receptor targets. In silico validation of virtual screening protocols before application to a receptor target using a corporate or commercially available compound collection is key to establishing a successful process. Ultimately, retrieval of a set of active compounds from a database of inactives is required, and the metric of enrichment (E) is habitually used to discern the quality of separation of the two. Numerous reports have addressed the performance of docking algorithms with regard to the quality of binding mode prediction and the issue of postprocessing "hit lists" of docked ligands. However, the impact of ligand database preprocessing has yet to be examined in the context of virtual screening and prioritization of compounds for biological evaluation. We provide an insight into the implications of cheminformatic preprocessing of a validation database of compounds where multiple protonated, tautomeric, stereochemical, and conformational states have been enumerated. Several commonly used methods for the generation of ligand conformations and conformational ensembles are examined, paired with an exhaustive rigid-body algorithm for the docking of different "multimeric" compound representations to the ligand binding site of the human estrogen receptor alpha. Chemgauss, a shapegaussian scoring function with intrinsic chemical knowledge, was combined with PLP as a consensus-scoring scheme to rank output from the docking protocol and enrichment rates calculated for each screen. The overheads of CPU consumption and the effect on relative database size (disk requirement) for each of the protocols employed are considered. Assessment of these parameters indicates that SBVS enrichments are highly dependent on the initial cheminformatic treatment(s) used in database construction. The interplay of SMILES representations, stereochemical information, protonation state enumeration, and ligand conformation ensembles are critical in achieving optimum enrichment rates in such screening.

Structure-activity studies with high-affinity inhibitors of pyroglutamyl-peptidase II.

Inhibitors of PPII (pyroglutamyl-peptidase II) (EC 3.4.19.6) have potential applications as investigative and therapeutic agents. The rational design of inhibitors is hindered, however, by the lack of an experimental structure for PPII. Previous studies have demonstrated that replacement of histidine in TRH (thyrotropin-releasing hormone) with asparagine produces a competitive PPII inhibitor (Ki 17.5 microM). To gain further insight into which functional groups are significant for inhibitory activity, we investigated the effects on inhibition of structural modifications to Glp-Asn-ProNH2 (pyroglutamyl-asparaginyl-prolineamide). Synthesis and kinetic analysis of a diverse series of carboxamide and C-terminally extended Glp-Asn-ProNH2 analogues were undertaken. Extensive quantitative structure-activity relationships were generated, which indicated that key functionalities in the basic molecular structure of the inhibitors combine in a unique way to cause PPII inhibition. Data from kinetic and molecular modelling studies suggest that hydrogen bonding between the asparagine side chain and PPII may provide a basis for the inhibitory properties of the asparagine-containing peptides. Prolineamide appeared to be important for interaction with the S2' subsite, but some modifications were tolerated. Extension of Glp-Asn-ProNH2 with hydrophobic amino acids at the C-terminus led to a novel set of PPII inhibitors active in vitro at nanomolar concentrations. Such inhibitors were shown to enhance recovery of TRH released from rat brain slices. Glp-Asn-Pro-Tyr-Trp-Trp-7-amido-4-methylcoumarin displayed a Ki of 1 nM, making it the most potent competitive PPII inhibitor described to date. PPII inhibitors with this level of potency should find application in exploring the biological functions of TRH and PPII, and potentially provide a basis for development of novel therapeutics.

A real-time EMG-driven virtual arm.

An EMG-driven virtual arm is being developed in our laboratories for the purposes of studying neuromuscular control of arm movements. The virtual arm incorporates the major muscles spanning the elbow joint and is used to estimate tension developed by individual muscles based on recorded electromyograms (EMGs). It is able to estimate joint moments and the corresponding virtual movements, which are displayed in real-time on a computer screen. In addition, the virtual arm offers artificial control over a variety of physiological and environmental conditions. The virtual arm can be used to examine how the neuromuscular system compensates for the partial or total loss of a muscle's ability to generate force as might result from trauma or pathology. The purpose of this paper is to describe the design objectives, fundamental components and implementation of our real-time, EMG-driven virtual arm.