Gestural Turing Test. A Motion-Capture Experiment for Exploring Believability In Artificial Nonverbal Communication.

One of the open problems in creating believable characters in computer games and collaborative virtual environments is simulating adaptive human-like motion. Classical artificial intelligence (AI) research places an emphasis on verbal language. In response to the limitations of classical AI, many researchers have turned their attention to embodied communication and situated intelligence. Inspired by Gestural Theory, which claims that speech emerged from visual, bodily gestures in primates, we implemented a variation of the Turing Test, using motion instead of text for messaging between agents. In doing this, we attempt to understand the qualities of motion that seem human-like to people. We designed two gestural AI algorithms that simulate or mimic communicative human motion using the positions of the head and the hands to determine three moving points as the signal. To run experiments, we implemented a networked-based architecture for a Vicon motion capture studio. Subjects were shown both artificial and human gestures, and were told to declare whether it was real or fake. Techniques such as simple gesture imitation were found to increase believability. While we require many such experiments to understand the perception of humanness in movement, we believe this research is essential to developing a truly believable character

Structural diversity of biologically interesting datasets: a scaffold analysis approach

ABSTRACT:The recent public availability of the human metabolome and natural product datasets has revitalized "metabolite-likeness" and "natural product-likeness" as a drug design concept to design lead libraries targeting specific pathways. Many reports have analyzed the physicochemical property space of biologically important datasets, with only a few comprehensively characterizing the scaffold diversity in public datasets of biological interest. With large collections of high quality public data currently available, we carried out a comparative analysis of current day leads with other biologically relevant datasets.In this study, we note a two-fold enrichment of metabolite scaffolds in drug dataset (42%) as compared to currently used lead libraries (23%). We also note that only a small percentage (5%) of natural product scaffolds space is shared by the lead dataset. We have identified specific scaffolds that are present in metabolites and natural products, with close counterparts in the drugs, but are missing in the lead dataset. To determine the distribution of compounds in physicochemical property space we analyzed the molecular polar surface area, the molecular solubility, the number of rings and the number of rotatable bonds in addition to four well-known Lipinski properties. Here, we note that, with only few exceptions, most of the drugs follow Lipinski's rule. The average values of the molecular polar surface area and the molecular solubility in metabolites is the highest while the number of rings is the lowest. In addition, we note that natural products contain the maximum number of rings and the rotatable bonds than any other dataset under consideration.Currently used lead libraries make little use of the metabolites and natural products scaffold space. We believe that metabolites and natural products are recognized by at least one protein in the biosphere therefore, sampling the fragment and scaffold space of these compounds, along with the knowledge of distribution in physicochemical property space, can result in better lead libraries. Hence, we recommend the greater use of metabolites and natural products while designing lead libraries. Nevertheless, metabolites have a limited distribution in chemical space that limits the usage of metabolites in library design.14 page(s

Setting our sights on infectious diseases

In May 2019, the Wellcome Centre for Anti-Infectives Research (WCAIR) at the University of Dundee, UK, held an international conference with the aim of discussing some key questions around discovering new medicines for infectious diseases and a particular focus on diseases affecting Low and Middle Income Countries. There is an urgent need for new drugs to treat most infectious diseases. We were keen to see if there were lessons that we could learn across different disease areas and between the preclinical and clinical phases with the aim of exploring how we can improve and speed up the drug discovery, translational, and clinical development processes. We started with an introductory session on the current situation and then worked backward from clinical development to combination therapy, pharmacokinetic/pharmacodynamic (PK/PD) studies, drug discovery pathways, and new starting points and targets. This Viewpoint aims to capture some of the learnings

Non-genomic effects of nuclear receptors: insights from the anucleate platelet

Nuclear receptors have the ability to elicit two different kinds of responses, genomic and non-genomic. While genomic responses control gene expression by influencing the rate of transcription, non-genomic effects occur rapidly and independently of transcriptional regulation. Due to their anucleate nature and mechanistically well-characterised and rapid responses, platelets provide a model system for the study of any non-genomic effects of the nuclear receptors. Several nuclear receptors have been found to be expressed in human platelets, and multiple nuclear receptor agonists have been shown to elicit anti-platelet effects by a variety of mechanisms. The non-genomic functions of NRs vary, including the regulation of kinase and phosphatase activity, ion channel function, intracellular calcium levels and production of second messengers. Recently, the characterisation of mechanisms and identification of novel binding partners of nuclear receptors have further strengthened the prospects of developing their ligands into potential therapeutics that offer cardio-protective properties in addition to their other defined genomic effects

A Comparative Chemogenomics Strategy to Predict Potential Drug Targets in the Metazoan Pathogen, Schistosoma mansoni

Schistosomiasis is a prevalent and chronic helmintic disease in tropical regions. Treatment and control relies on chemotherapy with just one drug, praziquantel and this reliance is of concern should clinically relevant drug resistance emerge and spread. Therefore, to identify potential target proteins for new avenues of drug discovery we have taken a comparative chemogenomics approach utilizing the putative proteome of Schistosoma mansoni compared to the proteomes of two model organisms, the nematode, Caenorhabditis elegans and the fruitfly, Drosophila melanogaster. Using the genome comparison software Genlight, two separate in silico workflows were implemented to derive a set of parasite proteins for which gene disruption of the orthologs in both the model organisms yielded deleterious phenotypes (e.g., lethal, impairment of motility), i.e., are essential genes/proteins. Of the 67 and 68 sequences generated for each workflow, 63 were identical in both sets, leading to a final set of 72 parasite proteins. All but one of these were expressed in the relevant developmental stages of the parasite infecting humans. Subsequent in depth manual curation of the combined workflow output revealed 57 candidate proteins. Scrutiny of these for ‘druggable’ protein homologs in the literature identified 35 S. mansoni sequences, 18 of which were homologous to proteins with 3D structures including co-crystallized ligands that will allow further structure-based drug design studies. The comparative chemogenomics strategy presented generates a tractable set of S. mansoni proteins for experimental validation as drug targets against this insidious human pathogen

Manipulation and sorting of membrane proteins using patterned diffusion-aided ratchets with AC fields in supported lipid bilayers

We present ratchets capable of directing the movement of charged components within supported bilayer lipid membranes. These ratchets make use of asymmetrically patterned features and AC electric fields, and have been demonstrated to transport charged species such as lipids and transmembrane proteins between two reservoirs. Proteins were present in both orientations in the membrane, with only those with their extra-membranous domain orientated away from the glass substrate being mobile. Proteins in the mobile orientation were transported using these ratchets, thereby sorting the two orientations from one another, and creating an area of the membrane containing five times more protein in one orientation than the other

Rapid Analysis of Pharmacology for Infectious Diseases

Pandemic, epidemic and endemic infectious diseases are united by a common problem: how do we rapidly and cost-effectively identify potential pharmacological interventions to treat infections? Given the large number of emerging and neglected infectious diseases and the fact that they disproportionately afflict the poorest members of the global society, new ways of thinking are required to develop high productivity discovery systems that can be applied to a large number of pathogens. The growing availability of parasite genome data provides the basis for developing methods to prioritize, a priori potential drug targets and analyze the pharmacological landscape of an infectious disease. Thus the overall objective of infectious disease informatics is to enable the rapid generation of plausible, novel medical hypotheses of test-able pharmacological experiments, by uncovering undiscovered relationships in the wealth of biomedical literature and databases that were collected for other purposes. In particular our goal is to identify potential drug targets present in a pathogen genome and prioritize which pharmacological experiments are most likely to discover drug-like lead compounds rapidly against a pathogen (i.e. which specific compounds and drug targets should be screened, in which assays and where they can be sourced). An integral part of the challenge is the development and integration of methods to predict druggability, essentiality, synthetic lethality and polypharmocology in pathogen genomes, while simultaneously integrating the inevitable issues of chemical tractability and the potential for acquired drug resistance from the start