BACKGROUND: Strategies to control HIV for improving the quality of patient lives have been aided by the Highly Active Anti-Retroviral Therapy (HAART), which consists of a cocktail of inhibitors targeting key viral enzymes. Numerous new drugs have been developed over the past few decades but viral resistances to these drugs in the targeted viral enzymes are increasingly reported. Nonetheless the acquired mutations often reduce viral fitness and infectivity. Viral compensatory secondary-line mutations mitigate this loss of fitness, equipping the virus with a broad spectrum of resistance against these drugs. While structural understanding of the viral protease and its drug resistance mutations have been well established, the interconnectivity and development of structural cross-resistance remain unclear. This paper reports the structural analyses of recent clinical mutations on the drug cross-resistance effects from various protease and protease inhibitors (PIs) complexes. METHODS: Using the 2015 updated clinical HIV protease mutations, we constructed a structure-based correlation network and a minimum-spanning tree (MST) based on the following features: (i) topology of the PI-binding pocket, (ii) allosteric effects of the mutations, and (iii) protease structural stability. RESULTS AND CONCLUSION: Analyis of the network and the MST of dominant mutations conferring resistance to the seven PIs (Atazanavir-ATV, Darunavir-DRV, Indinavir-IDV, Lopinavir-LPV, Nelfinavir-NFV, Saquinavir-SQV, and Tipranavir-TPV) showed that cross-resistance can develop easily across NFV, SQV, LPV, IDV, and DRV, but not for ATV or TPV. Through estimation of the changes in vibrational entropies caused by each reported mutation, some secondary mutations were found to destabilize protease structure. Our findings provide an insight into the mechanism of PI cross-resistance and may also be useful in guiding the selection of PI in clinical treatment to delay the onset of cross drug resistance.

SUMMARY: There have been numerous applications developed for decoding and visualization of ab1 DNA sequencing files for Windows and MAC platforms, yet none exists for the increasingly popular smartphone operating systems. The ability to decode sequencing files cannot easily be carried out using browser accessed Web tools. To overcome this hurdle, we have developed a new native app called DNAApp that can decode and display ab1 sequencing file on Android and iOS. In addition to in-built analysis tools such as reverse complementation, protein translation and searching for specific sequences, we have incorporated convenient functions that would facilitate the harnessing of online Web tools for a full range of analysis. Given the high usage of Android/iOS tablets and smartphones, such bioinformatics apps would raise productivity and facilitate the high demand for analyzing sequencing data in biomedical research. AVAILABILITY AND IMPLEMENTATION: The Android version of DNAApp is available in Google Play Store as 'DNAApp', and the iOS version is available in the App Store. More details on the app can be found at www.facebook.com/APDLab; www.bii.a-star.edu.sg/research/trd/apd.php The DNAApp user guide is available at http://tinyurl.com/DNAAppuser, and a video tutorial is available on Google Play Store and App Store, as well as on the Facebook page. CONTACT: [email protected].