Conferences system

Пятница, 16 декабря 2011 года, 18:00, Москва, МГУ, лабораторный корпус «Б», 2-й этаж, комната 221

Тема заседания — доклад Кася Бозек (Kasia Bożek), Max Planck Institute for Computer Sciences, Saarbrücken (now at PICB, Shanghai);
«Физико-химические и структурные свойства, определяющие использование корецепторов ВИЧ-1» («Physicochemical and structural properties determining HIV-1 coreceptor usage»)

The entry of the human immunodeficiency virus (HIV) into human cells is a multi step process involving binding to one of the cell-surface coreceptors CCR5 or CXCR4. The binding site of the coreceptor is partially situated on the third variable region (V3) of gp120 viral protein. Whether a virus can bind to CCR5 only (R5 virus), to CCR5 and CXCR4 alternately (dual virus) or to CXCR4 only (X4 virus) is determined predominantly by the sequence and structure of this region. The phenotype related to the virus coreceptor usage is termed viral tropism. While in the early, asymptomatic stages of infection mainly R5 viruses are observed, progression to AIDS is often correlated with the emergence of X4 viruses. The relationship of HIV tropism with disease progression and the recent development of CCR5-blocking drugs underscore the importance of monitoring virus coreceptor usage. As an alternative to costly phenotypic assays, computational methods aim at predicting virus tropism based on the V3 loop sequence of the virus gp120 protein and on its structure. The major drawback of the binary sequence representation is that it offers insights into the physicochemical properties of amino acids and their spatial arrangement in the binding site that determines coreceptor binding.

Here we present a structural descriptor of the V3 loop encoding the physicochemical properties of the loop together with their locations on the protein structure. We map 54 amino acid indices representing the physicochemical properties of amino acids onto the V3 loop structure and use machine learning methods to extract the features which are the most informative for coreceptor usage. The extracted set of features represents a small fraction of the initial feature set and models based on this set attain higher prediction accuracy with decreased computational load.

Our descriptor used as input to the support vector machine predicting tropism shows a statistically significant improvement over the binary representation of the V3 sequence. At the specificity of 11/25 rule a sensitivity of 69% was achieved, comparing favorably with the 62% sensitivity of sequence-based prediction. In addition to the data inferred from lab-cloned viruses (clonal data) we assessed the predictive power of our method on the clinically derived 'bulk' sequence data of patient samples and obtained a statistically significant 3% improvement over the sequence representation evaluated using receiver operating characteristic (ROC) curve. We also demonstrated the capacity of our method to predict the outcome of the coreceptor blocker-based therapy by applying it to 53 samples of patients undergoing Maraviroc therapy.

Our structural descriptor affords direct interpretation of the features of the V3 loop relevant for viral tropism by pointing to specific physicochemical properties of amino acids in specific parts of the loop being predictive of coreceptor usage. The analysis of features important for the classification pointed to two loop regions and their physicochemical properties playing determining role in the coreceptor usage. The regions are located on the opposite strands of the loop stem; and show predominantly structure, hydrophobicity and charge-related properties. These regions are in close proximity in the bound conformation of the loop forming a potentially determinant site for the coreceptor usage. The resulting method offers higher performance over sequence-based method with a comparable efficiency and a direct interpretation of structural and physicochemical determinants of tropism

Рабочий язык семинара — английский.

Адрес:
Москва, МГУ, лабораторный корпус «Б» (факультет биоинженерии и биоинформатики), комната 221 (2 этаж, направо по коридору).
Проезд: Станция метро Университет, автобусы 187, 260, 130, 103, 113, 661, 47 или троллейбус 34 до остановки: «Улица Менделеевская».
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