Muhammad Ahsan

VacSol: a high throughput in silico pipeline to predict potential therapeutic targets in prokaryotic pathogens using subtractive reverse vaccinology

BackgroundWith advances in reverse vaccinology approaches, a progressive improvement has been observed in the prediction of putative vaccine candidates. Reverse vaccinology has changed the way of discovery and provides a mean to propose target identification in reduced time and labour. In this regard, high throughput genomic sequencing technologies and supporting bioinformatics tools have greatly facilitated the prompt analysis of pathogens, where various predicted candidates have been found effective against certain infections and diseases. A pipeline, VacSol, is designed here based on a similar approach to predict putative vaccine candidates both rapidly and efficiently.ResultsVacSol, a new pipeline introduced here, is a highly scalable, multi-mode, and configurable software designed to automate the high throughput in silico vaccine candidate prediction process for the identification of putative vaccine candidates against the proteome of bacterial pathogens. Vaccine candidates are screened using integrated, well-known and robust algorithms/tools for proteome analysis, and the results from the VacSol software are presented in five different formats by taking proteome sequence as input in FASTA file format. The utility of VacSol is tested and compared with published data and using the Helicobacter pylori 26695 reference strain as a benchmark.ConclusionVacSol rapidly and efficiently screens the whole bacterial pathogen proteome to identify a few predicted putative vaccine candidate proteins. This pipeline has the potential to save computational costs and time by efficiently reducing false positive candidate hits. VacSol results do not depend on any universal set of rules and may vary based on the provided input. It is freely available to download from: https://sourceforge.net/projects/vacsol/.

Robust Output Feedback Stabilization of a Magnetic Levitation System Using Higher Order Sliding Mode Control Strategy

This work studies the problem of robust output feedback stabilization of a Magnetic Levitation System using Higher Order Sliding Mode Control (HOSMC) strategy. The traditional (first order) sliding mode control (SMC) design tool provides for a systematic approach to solving the problem of stabilization and maintaining a predefined (user specified) consistent performance of a minimum-phase nonlinear system in the face of modeling imprecision and parametric uncertainties. Recently reported variants of SMC commonly known as Higher Order Sliding Mode Control schemes have gained substantial attention since these provide for a better transient performance together with robustness properties. In this work, we focus on design of an output feedback controller that robustly stabilizes a Magnetic Levitation System with an added objective of achieving an improvement in the transient performance. The proposed control scheme incorporates a higher-order sliding mode controller (HOSMC) to solve the robust semi-global stabilization problem in presence of a class of somewhat unknown disturbances and parametric uncertainties. The state feedback control design is extended to output feedback by including a high gain observer that estimates the unmeasured states. It is shown that by suitable choice of observer gains, the output feedback controller recovers the performance of state feedback and achieves semi-global stabilization over a domain of interest. A detailed analysis of the closed-loop system is given highlighting the various factors that lead to improvement in transient performance, robustness properties and elimination of chattering. Simulation results are included and a performance comparison is given for the traditional SMC and HOSMC designs employing the first and second order sliding modes in the controller structure.