Concentración espacial de las denuncias por violencia familiar en Ciudad Victoria: un acercamiento mediante la detección de hot spots / Spatial concentration of complaints of family violence in Ciudad Victoria: an approach through the detection of hot spots

Resumen La violencia familiar es el principal delito cometido a nivel nacional en México. Tamaulipas tiene una tasa de denuncias que se encuentra por encima de la media nacional desde el año 2016 hasta el 2018, destacando el municipio de Vitoria con la tasa más alta en ese período. El objetivo de este trabajo fue identificar la concentración espacial de las denuncias por violencia familiar en Ciudad Victoria y especificar la relación entre las desventajas del vecindario y la ubicación en un hot spot (punto caliente). El estudio se basa en la teoría de la desorganización social y tiene como soporte los datos de la Fiscalía General del Estado de Tamaulipas en el periodo 2016-2018. Para ello, se desarrolló el análisis exploratorio de datos espaciales mediante las técnicas de estimación de densidad de kernel, promedio del vecino más cercano, análisis de hot spot Gi* de Getis-Ord y un análisis confirmatorio mediante una regresión logística binaria, procesamientos desarrollados en el software ArcMap 10.8.1 y en el paquete estadístico R. Los hallazgos indicaron que las denuncias se producen desde un número reducido de unidades geográficas. La prueba del promedio del vecino más cercano mostró que existe agrupamiento estadísticamente significativo (z = - 10.825, P = 0.000). En el análisis Gi* de Getis-Ord se detectó que 602 manzanas (9.8 % del total) son hot spots (al 95 % y 99 % de confianza) de alta incidencia, mientras que la regresión logística confirmó que la cantidad de ocupantes por vivienda y los hogares con jefatura femenina están asociados positivamente con la probabilidad de estar dentro de un hot spot de violencia familiar. El patrón de denuncias mostró poca dispersión geográfica y asociación estadística relevante con las variables de desorganización social.

Abstract The main crime committed in Mexico is domestic violence. Tamaulipas had a reporting rate above the national average from 2016 to 2018, with Ciudad Victoria having the highest rate during that period. The objective of this work is to identify the spatial concentration of complaints on family violence and to specify the relationship between the neighborhood characteristics and its location in a hot spot. To that aim, the study uses the social disorganization theory and data of complaints taken from the Fiscalia General del Estado de Tamaulipas during the 2016-2018 period. The exploratory analysis of spatial data was developed by using kernel density estimation techniques, nearest neighbor average, Getis-Ord Gi* hot spot analysis and confirmatory analysis through binary logistic regression, with the help of the ArcMap 10.8.1 software and R statistical package. The findings indicated that complaints of domestic violence are produced from a small number of geographic units. The nearest neighbor mean test showed that there is a statistically significant grouping of complaints (z = - 10.825, P = 0.000). In the Gi * analysis of Getis-Ord, 602 blocks (9.8 % of the total) were identified as hot spots (at 95 % and 99 % confidence), while the logistic regression confirmed that the number of occupants per dwelling and households headed by women are positively associated with the probability of being in a hot spot of family violence. The pattern of the complaints showed little geographic dispersion and relevant statistical associations with the social disorganization variables.

DHODH Hot Spots: An Underexplored Source to Guide Drug Development Efforts.

BACKGROUND: Dihydroorotate dehydrogenase (DHODH) has long been recognized as an important drug target for proliferative and parasitic diseases, including compounds that exhibit trypanocidal action and broad-spectrum antiviral activity. Despite numerous and successful efforts in structural and functional characterization of DHODHs, as well as in the development of inhibitors, DHODH hot spots remain largely unmapped and underexplored. OBJECTIVE: This review describes the tools that are currently available for the identification and characterization of hot spots in protein structures and how freely available webservers can be exploited to predict DHODH hot spots. Moreover, it provides for the first time a review of the antiviral properties of DHODH inhibitors. METHODS: X-ray structures from human (HsDHODH) and Trypanosoma cruzi DHODH (TcDHODH) had their hot spots predicted by both FTMap and Fragment Hotspot Maps web servers. RESULTS: FTMap showed that hot spot occupancy in HsDHODH is correlated with the ligand efficiency (LE) of its known inhibitors, and Fragment Hotspot Maps pointed out the contribution of selected moieties to the overall LE. The conformational flexibility of the active site loop in TcDHODH was found to have a major impact on the druggability of the orotate binding site. In addition, both FTMap and Fragment Hotspot Maps servers predict a novel pocket in TcDHODH dimer interface (S6 site). CONCLUSION: This review reports how hot spots can be exploited during hit-to-lead steps, docking studies or even to improve inhibitor binding profile and by doing so using DHODH as a model, points to new drug development opportunities.

Analysis of HPV Integrations in Mexican Pre-Tumoral Cervical Lesions Reveal Centromere-Enriched Breakpoints and Abundant Unspecific HPV Regions.

Human papillomavirus (HPV) DNA integration is a crucial event in cervical carcinogenesis. However, scarce studies have focused on studying HPV integration (HPVint) in early-stage cervical lesions. Using HPV capture followed by sequencing, we investigated HPVint in pre-tumor cervical lesions. Employing a novel pipeline, we analyzed reads containing direct evidence of the integration breakpoint. We observed multiple HPV infections in most of the samples (92%) with a median integration rate of 0.06% relative to HPV mapped reads corresponding to two or more sequence breakages. Unlike cancer studies, most integrations events were unique (supported by one read), consistent with the lack of clonal selection. Congruent to other studies, we found that breakpoints could occur, practically, in any part of the viral genome. We noted that L1 had a higher frequency of rupture integration (25%). Based on host genome integration frequencies, we found previously reported integration sites in cancer for genes like FHIT, CSMD1, and LRP1B and putatively many new ones such as those exemplified in CSMD3, ROBO2, and SETD3. Similar host integrations regions and genes were observed in diverse HPV types within many genes and even equivalent integration positions in different samples and HPV types. Interestingly, we noted an enrichment of integrations in most centromeres, suggesting a possible mechanism where HPV exploits this structural machinery to facilitate integration. Supported by previous findings, overall, our analysis provides novel information and insights about HPVint.

When informal work and poor work conditions backfire and fuel the COVID-19 pandemic: Why we should listen to the lessons from Latin America.

Latin America is among the regions with the highest incidence of COVID-19 where the pandemic is creating a humanitarian crisis. In this Commentary we aim to reveal underlying problems of this crisis, that may be an underestimated global driver of the pandemic and a serious risk to health and healthcare systems. We set the focus on informal work and related poorly regulated sub-contracting which create poor work conditions as one dimension of the social determinants of health. We use the examples of Germany and Brazil, as opposite sides geographically and concerning the pandemic, to highlight a need for greater attention to these risks and for systematic inclusion in health systems resilience. In both countries, informal work may turn into hot spots of COVID-19, thus reinforcing social inequalities on a grand scale both nationally and globally. Our two contrasting country cases thus reveal a global threat that should be treated as such. There is much to learn for Europe and the world from Brazil and Latin America on what happens when informal labour and poor work environments backfire during the COVID-19 pandemic. We should listen carefully to these lessons.

Analysis of incidence of air quality on human health: a case study on the relationship between pollutant concentrations and respiratory diseases in Kennedy, Bogotá.

Thousands of deaths associated with air pollution each year could be prevented by forecasting the behavior of factors that pose risks to people's health and their geographical distribution. Proximity to pollution sources, degree of urbanization, and population density are some of the factors whose spatial distribution enables the identification of possible influence on the presence of respiratory diseases (RD). Currently, Bogotá is among the cities with the poorest air quality in Latin America. Specifically, the locality of Kennedy is one of the zones in the city with the highest recorded concentration levels of local pollutants over the last 10 years. From 2009 to 2016, there were 8619 deaths associated with respiratory and cardiovascular diseases in the locality. Given these characteristics, this study set out to identify and analyze the areas in which the primary socioeconomic and environmental conditions contribute to the presence of symptoms associated with RD. To this end, information collected in field by performing georeferenced surveys was analyzed through geostatistical and machine learning tools which carried out cluster and pattern analyses. Random forests and AdaBoost were applied to establish hot spots where RD could occur, given the conjugation of predictor variables in the micro-territory. It was found that random forests outperformed AdaBoost with 0.63 AUC. In particular, this study's approach applies to densely populated municipalities with high levels of air pollution. In using these tools, municipalities can anticipate environmental health situations and reduce the cost of respiratory disease treatments.

Distribution and habitat use intensity of the Neotropical Otter (Lontra longicaudis) in a Colombian hydroelectric dam / Distribución e intensidad de uso del hábitat de la nutria neotropical (Lontra longicaudis Olfers, 1818) en una represa hidroeléctrica colombiana

Introduction: The Neotropical Otter, Lontra longicaudis, is a semi-aquatic mammal that ranges from Mexico to Argentina inhabiting near-pristine watercourses, but also human-dominated aquatic and riparian landscapes. Objective: We assessed the distribution and habitat use frequency of L. longicaudis in La Miel I hydroelectric power dam and its influence area in the Department of Caldas, Colombia. Methods: We carried out diurnal surveys across standardized transects between 2014 and 2018 looking for records (sightings, faeces, tracks, and dens) that indicate the presence of the species. Each yearly survey was done during 12 consecutive days over three seasonal sampling periods assessing the upstream, reservoir, and downstream waterscape areas. Results: We sampled a total of 875 km in a five-year period across the three main waterscape areas (upstream -103 km, reservoir -582 km, and downstream -190 km) registering a total of 1 496 records. Faeces were the most common record (~ 95 %) across the whole study area followed by sightings, dens (1.7 % each), and tracks (1.3 %). Spatial distribution analyses suggest that L. longicaudis prefers dwelling upstream watercourses (hot spots areas; Gi Z-score = 4.46, p < 0.001) and in a lesser extent, areas around the water reservoir (cold spot areas; Gi Z-score = -2.69, p = 0.007). Signs of otters were also recorded at downstream area, but these records were non-significant within the analysis (Gi Z-score = -0.11, p = 0.48), suggesting L. longicaudis uses this area opportunistically. Cluster and outlier analysis showed that even though L. longicaudis was commonly found upstream and in the reservoir area, only some specific sectors (Moro, La Miel and Tasajos rivers) had high (LMI Z-score = 5.63, p = 0.001) and low (LMI Z-score = 2.12, p = 0.001) clusters. Conclusions: The upstream waterscape area is key for the survival of L. longicaudis in this regulated system, likely providing enough shelter and food for the species to carry out living activities and have resident populations. In contrast, downstream areas require specific attention to understand in a better way the effects of caused by the dam on the species dynamics, also defining management strategies that avoid population fragmentation and movement reduction.

Introducción : La nutria neotropical Lontra longicaudis, es un mamífero semiacuático que se distribuye desde México hasta Argentina; habita en paisajes acuáticos y ribereños prístinos, pero también hábitats dominados por el hombre. Objetivo : Se evaluó la distribución e intensidad de uso del hábitat de L. longicaudis en la hidroeléctrica La Miel I y su área de influencia en el Departamento de Caldas, Colombia. Métodos: Se realizaron transectos diurnos estandarizados entre 2014 y 2018 en busca de registros (avistamientos, heces, huellas y madrigueras) que indicaban la presencia de la especie. Cada muestreo anual se realizó durante 12 días consecutivos en tres períodos de muestreo estacional (36 días), evaluando las áreas aguas arriba, el embalse y aguas abajo de la presa. Resultados : Se muestreó un total de 875 km a través de las tres áreas principales con un total de 1 496 rastros. Las heces fueron el registro más común (~ 95 %) en toda el área de estudio, seguido de avistamientos, madrigueras (1.7 % cada una), y huellas (1.3 %). Los análisis de distribución espacial sugieren que L. longicaudis prefiere los afluentes aguas arriba (áreas de puntos calientes; Gi Z-score = 4.46, p < 0.001) y, en menor medida, las zonas alrededor del embalse (áreas de puntos fríos; Gi Z-score = -2.69, p = 0.007). El área aguas abajo también mostró presencia de nutrias; sin embargo, esos registros no fueron significativos dentro del análisis (Gi Z-score = -0.11, p = 0.48), sugiriendo que L. longicaudis usa esta área esporádicamente. El análisis de conglomerados y datos atípicos mostró que, aunque L. longicaudis se encuentra comúnmente aguas arriba y en el área del embalse, solo algunos sectores específicos (ríos Moro, La Miel y Tasajos) tienen valores altos (LMI Z-score = 5.63, p= 0.001) y bajos (LMI Z-score = 2.12, p = 0.001) de conglomerados. Conclusiones : El paisaje y las características hidrológicas aguas arriba son claves para la supervivencia de la nutria neotropical en este sistema regulado, probablemente aportando suficiente refugio y alimento para que la especie lleve a cabo sus actividades vitales, permitiéndole tener poblaciones residentes. Se debe enfocar la atención en la zona aguas abajo para comprender el efecto de la presa en la dinámica de la especie, definiendo estrategias de manejo que eviten la fragmentación de la población y la reducción de los movimientos.

Nucleation-dependent amyloid fibrillation of human GRASP55 in aqueous solution.

GRASP55, one of the two human GRASP proteins, has been implicated in the organization of Golgi stacks and in unconventional protein secretion. However, the detailed molecular mechanisms supporting GRASP55 participation in those processes remain mostly unclear. We have shown that GRASP55 exists as monomers in solution, which transitions to amorphous aggregates with increasing temperatures. Here, we further investigated the formation of higher order structures of GRASP55 by exploring its amyloid fibrillation at 37 °C. Sequence-based AGGRESCAN analysis revealed that GRASP55 has ten aggregation "hot spots", preferentially concentrated in its N-terminal half. Congo Red, ThT, and circular dichroism assays suggested GRASP55 formed amyloid-like fibrils in a time-dependent manner at 37 °C. Dynamic light scattering showed the mean hydrodynamic radius of GRASP55 amyloid-like fibrils increased with increasing incubation times at 37 °C. Transmission electron microscopy and intrinsic fluorescence lifetime imaging showed that, upon increasing incubation time at 37 °C, GRASP55 yielded amyloid-like fibrils in a nucleation-dependent process via a sequence of events: lag-phase (monomers to oligomers), growth phase (oligomers to organized protofibrils), and plateau phase (protofibrils to amyloid-like fibrils). The insights gained herein may help in better understanding the mechanisms of GRASP55 amyloid fibrillation in vivo and its potential association with neurological disorders.

Silver-based surface enhanced Raman spectroscopy devices for detection of organophosphorus pesticides traces.

The detection of traces of substances by surface-sensitive techniques such as surface enhanced Raman spectroscopy (SERS) explores the interaction of adsorbed molecules on plasmonic surfaces to improve the limit of detection of analytes. This article is an overview about recent development in SERS substrates applied in the detection of organophosphorus pesticides on plasmonic surfaces (arrays of metal nanoparticles). The morphology, roughness, chemical functionalization degree, and aggregation level of plasmonic centers are some of the critical parameters to be controlled in the optimization of SERS signal from specific analytes.

Spatiotemporal variation in fire occurrence in the state of Amazonas, Brazil, between 2003 and 2016 / Variação espaço-temporal da ocorrência de queimadas e incêndios florestais no estado do Amazonas, Brasil, entre 2003 e 2016

Wildland fires can be responsible for negative impacts on the environment, causing damage to the fauna and flora and increasing the release of greenhouse gases. In the state of Amazonas, wildland fires represent a risk for biodiversity conservation, since more than 95% of the state is covered by Amazon rainforest, one of the largest and most biodiverse tropical forests of the world. This study aimed to analyze the spatiotemporal variation of fire occurrence from 2003 to 2016 in the state of Amazonas, based on data from the AQUA satellite processed by the Brazilian National Institute for Space Research, using the Collection 5 detection algorithm. The correlation between fire incidence versus anthropogenic and climatic variables was also tested. A significant uptrend was observed in the number of hot spots recorded over the years. About 83% of the wildland fires occurred during the months of August, September and October. The variables that correlated significantly with the number of hot spots for each municipality were deforested area, pasture area, agricultural area, municipality area and mean annual rainfall. The municipality with the highest number of hot spots detected was Lábrea, while Careiro da Várzea presented the highest incidence per km2. The southern and eastern regions of the state were the areas most affected by fire during the analyzed period. The results from this study emphasize the need for implementation of public policies aimed to reduce deforestation and wildland fires in the state, thus ensuring the conservation of the Amazon rainforest and its biodiversity.(AU)

As queimadas controladas e incêndios florestais podem ser responsáveis por impactos negativos ao meio ambiente, ocasionando danos à fauna e flora e contribuindo para a liberação de gases na atmosfera responsáveis pelo efeito estufa. O fogo no Amazonas representa um grande risco para a preservação da biodiversidade, já que mais de 95% da área do estado é recoberta por floresta amazônica, uma das maiores florestas tropicais do mundo. Este trabalho teve por objetivo analisar a variação espaço-temporal dos focos de calor registrados de 2003 a 2016 no estado do Amazonas, com base em dados obtidos através do satélite AQUA e processados pelo INPE, utilizando o algoritmo de detecção Collection 5. Os dados de focos de calor foram correlacionados com variáveis antropogênicas e climáticas. Foi observada uma tendência significativa de alta nos registros de focos de calor ao longo dos anos. Cerca de 83% das detecções ocorreram nos meses de Agosto, Setembro e Outubro. As variáveis área desmatada, área de pastagem, área agrícola, área do município e precipitação média anual apresentaram correlação significativa com o número de focos de calor para cada município. O município com maior registro de focos de calor foi Lábrea, enquanto Careiro da Várzea apresentou a maior incidência por área. Os resultados obtidos ressaltam a necessidade de implementação de políticas públicas que visem a redução do desmatamento e dos incêndios florestais no estado, garantindo a preservação da floresta amazônica e sua biodiversidade.(AU)

Spatiotemporal variation in fire occurrence in the state of Amazonas, Brazil, between 2003 and 2016 / Variação espaço-temporal da ocorrência de queimadas e incêndios florestais no estado do Amazonas, Brasil, entre 2003 e 2016

Wildland fires can be responsible for negative impacts on the environment, causing damage to the fauna and flora and increasing the release of greenhouse gases. In the state of Amazonas, wildland fires represent a risk for biodiversity conservation, since more than 95% of the state is covered by Amazon rainforest, one of the largest and most biodiverse tropical forests of the world. This study aimed to analyze the spatiotemporal variation of fire occurrence from 2003 to 2016 in the state of Amazonas, based on data from the AQUA satellite processed by the Brazilian National Institute for Space Research, using the Collection 5 detection algorithm. The correlation between fire incidence versus anthropogenic and climatic variables was also tested. A significant uptrend was observed in the number of hot spots recorded over the years. About 83% of the wildland fires occurred during the months of August, September and October. The variables that correlated significantly with the number of hot spots for each municipality were deforested area, pasture area, agricultural area, municipality area and mean annual rainfall. The municipality with the highest number of hot spots detected was Lábrea, while Careiro da Várzea presented the highest incidence per km2. The southern and eastern regions of the state were the areas most affected by fire during the analyzed period. The results from this study emphasize the need for implementation of public policies aimed to reduce deforestation and wildland fires in the state, thus ensuring the conservation of the Amazon rainforest and its biodiversity.

As queimadas controladas e incêndios florestais podem ser responsáveis por impactos negativos ao meio ambiente, ocasionando danos à fauna e flora e contribuindo para a liberação de gases na atmosfera responsáveis pelo efeito estufa. O fogo no Amazonas representa um grande risco para a preservação da biodiversidade, já que mais de 95% da área do estado é recoberta por floresta amazônica, uma das maiores florestas tropicais do mundo. Este trabalho teve por objetivo analisar a variação espaço-temporal dos focos de calor registrados de 2003 a 2016 no estado do Amazonas, com base em dados obtidos através do satélite AQUA e processados pelo INPE, utilizando o algoritmo de detecção Collection 5. Os dados de focos de calor foram correlacionados com variáveis antropogênicas e climáticas. Foi observada uma tendência significativa de alta nos registros de focos de calor ao longo dos anos. Cerca de 83% das detecções ocorreram nos meses de Agosto, Setembro e Outubro. As variáveis área desmatada, área de pastagem, área agrícola, área do município e precipitação média anual apresentaram correlação significativa com o número de focos de calor para cada município. O município com maior registro de focos de calor foi Lábrea, enquanto Careiro da Várzea apresentou a maior incidência por área. Os resultados obtidos ressaltam a necessidade de implementação de políticas públicas que visem a redução do desmatamento e dos incêndios florestais no estado, garantindo a preservação da floresta amazônica e sua biodiversidade.

The potential of volunteered geographic information to investigate peri-urbanization in the conservation zone of Mexico City.

Due to the availability of Web 2.0 technologies, volunteered geographic information (VGI) is on the rise. This new type of data is available on many topics and on different scales. Thus, it has become interesting for research. This article deals with the collective potential of VGI and remote sensing to detect peri-urbanization in the conservation zone of Mexico City. On the one hand, remote sensing identifies horizontal urban expansion, and on the other hand, VGI of ecological complaints provides data about informal settlements. This enables the combination of top-down approaches (remote sensing) and bottom-up approaches (ecological complaints). Within the analysis, we identify areas of high urbanization as well as complaint densities and bring them together in a multi-scale analysis using Geographic Information Systems (GIS). Furthermore, we investigate the influence of settlement patterns and main roads on the peri-urbanization process in Mexico City using OpenStreetMap. Peri-urbanization is detected especially in the transition zone between the urban and rural (conservation) area and near main roads as well as settlements.

Interpreting T-Cell Cross-reactivity through Structure: Implications for TCR-Based Cancer Immunotherapy.

Immunotherapy has become one of the most promising avenues for cancer treatment, making use of the patient's own immune system to eliminate cancer cells. Clinical trials with T-cell-based immunotherapies have shown dramatic tumor regressions, being effective in multiple cancer types and for many different patients. Unfortunately, this progress was tempered by reports of serious (even fatal) side effects. Such therapies rely on the use of cytotoxic T-cell lymphocytes, an essential part of the adaptive immune system. Cytotoxic T-cells are regularly involved in surveillance and are capable of both eliminating diseased cells and generating protective immunological memory. The specificity of a given T-cell is determined through the structural interaction between the T-cell receptor (TCR) and a peptide-loaded major histocompatibility complex (MHC); i.e., an intracellular peptide-ligand displayed at the cell surface by an MHC molecule. However, a given TCR can recognize different peptide-MHC (pMHC) complexes, which can sometimes trigger an unwanted response that is referred to as T-cell cross-reactivity. This has become a major safety issue in TCR-based immunotherapies, following reports of melanoma-specific T-cells causing cytotoxic damage to healthy tissues (e.g., heart and nervous system). T-cell cross-reactivity has been extensively studied in the context of viral immunology and tissue transplantation. Growing evidence suggests that it is largely driven by structural similarities of seemingly unrelated pMHC complexes. Here, we review recent reports about the existence of pMHC "hot-spots" for cross-reactivity and propose the existence of a TCR interaction profile (i.e., a refinement of a more general TCR footprint in which some amino acid residues are more important than others in triggering T-cell cross-reactivity). We also make use of available structural data and pMHC models to interpret previously reported cross-reactivity patterns among virus-derived peptides. Our study provides further evidence that structural analyses of pMHC complexes can be used to assess the intrinsic likelihood of cross-reactivity among peptide-targets. Furthermore, we hypothesize that some apparent inconsistencies in reported cross-reactivities, such as a preferential directionality, might also be driven by particular structural features of the targeted pMHC complex. Finally, we explain why TCR-based immunotherapy provides a special context in which meaningful T-cell cross-reactivity predictions can be made.

Protein-protein interaction inhibitors: advances in anticancer drug design.

INTRODUCTION: Pocket-based drug design has contributed to major scientific breakthroughs in pharmaceutical research and development (R&D). The integrated use of experimental and computational methods, primarily during the early phases of drug discovery, has enabled the development of highly potent and selective small-molecule ligands. In this scenario, the targeting of protein-protein interactions (PPIs) has emerged as an attractive strategy for designing innovative drugs for highly complex diseases, such as cancer. AREAS COVERED: This article focuses on the use of experimental and computational approaches with a diversity of PPI classes and discusses the relevant advances in the field, primarily for oncological applications. Analyses of the target binding pockets and medicinal chemistry approaches used to develop promising PPI inhibitors are provided, with an emphasis on data reported over the past 2 years. EXPERT OPINION: PPI drug discovery is a challenging field that depends completely on accurate structural data. The integration of molecular docking, nuclear magnetic resonance and X-ray crystallography is a cornerstone for the current development of effective PPI inhibitors. Although this field has not reached its peak, several compounds have entered clinical trials over the past few years, providing promising perspectives for novel therapies for highly prevalent and life-threatening conditions.

Prediction of binding hot spot residues by using structural and evolutionary parameters.

In this work, we present a method for predicting hot spot residues by using a set of structural and evolutionary parameters. Unlike previous studies, we use a set of parameters which do not depend on the structure of the protein in complex, so that the predictor can also be used when the interface region is unknown. Despite the fact that no information concerning proteins in complex is used for prediction, the application of the method to a compiled dataset described in the literature achieved a performance of 60.4%, as measured by F-Measure, corresponding to a recall of 78.1% and a precision of 49.5%. This result is higher than those reported by previous studies using the same data set.

Prediction of binding hot spot residues by using structural and evolutionary parameters

In this work, we present a method for predicting hot spot residues by using a set of structural and evolutionary parameters. Unlike previous studies, we use a set of parameters which do not depend on the structure of the protein in complex, so that the predictor can also be used when the interface region is unknown. Despite the fact that no information concerning proteins in complex is used for prediction, the application of the method to a compiled dataset described in the literature achieved a performance of 60.4 percent, as measured by F-Measure, corresponding to a recall of 78.1 percent and a precision of 49.5 percent. This result is higher than those reported by previous studies using the same data set.