Non-Cryogenic Structure and Dynamics of HIV-1 Integrase Catalytic Core Domain by X-ray Free-Electron Lasers

Room temperature XFEL crystallography reveals asymmetry in the vicinity of the two phylloquinones in photosystem I

Photosystem I (PS I) has a symmetric structure with two highly similar branches of pigments at the center that are involved in electron transfer, but shows very different efficiency along the two branches. We have determined the structure of cyanobacterial PS I at room temperature (RT) using femtosecond X-ray pulses from an X-ray free electron laser (XFEL) that shows a clear expansion of the entire protein complex in the direction of the membrane plane, when compared to previous cryogenic structures. This trend was observed by complementary datasets taken at multiple XFEL beamlines. In the RT structure of PS I, we also observe conformational differences between the two branches in the reaction center around the secondary electron acceptors A_1A and A_1B. The π-stacked Phe residues are rotated with a more parallel orientation in the A-branch and an almost perpendicular confirmation in the B-branch, and the symmetry breaking PsaB-Trp673 is tilted and further away from A_1A. These changes increase the asymmetry between the branches and may provide insights into the preferential directionality of electron transfer.

Classification and Design of HIV-1 Integrase Inhibitors Based on Machine Learning

A key enzyme in human immunodeficiency virus type 1 (HIV-1) life cycle, integrase (IN) aids the integration of viral DNA into the host DNA, which has become an ideal target for the development of anti-HIV drugs. A total of 1785 potential HIV-1 IN inhibitors were collected from the databases of ChEMBL, Binding Database, DrugBank, and PubMed, as well as from 40 references. The database was divided into the training set and test set by random sampling. By exploring the correlation between molecular descriptors and inhibitory activity, it is found that the classification and specific activity data of inhibitors can be more accurately predicted by the combination of molecular descriptors and molecular fingerprints. The calculation of molecular fingerprint descriptor provides the additional substructure information to improve the prediction ability. Based on the training set, two machine learning methods, the recursive partition (RP) and naive Bayes (NB) models, were used to build the classifiers of HIV-1 IN inhibitors. Through the test set verification, the RP technique accurately predicted 82.5% inhibitors and 86.3% noninhibitors. The NB model predicted 88.3% inhibitors and 87.2% noninhibitors with correlation coefficient of 85.2%. The results show that the prediction performance of NB model is slightly better than that of RP, and the key molecular segments are also obtained. Additionally, CoMFA and CoMSIA models with good activity prediction ability both were constructed by exploring the structure-activity relationship, which is helpful for the design and optimization of HIV-1 IN inhibitors.

EM-detwin: A Program for Resolving Indexing Ambiguity in Serial Crystallography Using the Expectation-Maximization Algorithm

Serial crystallography (SX), first used as an application of X-ray free-electron lasers (XFELs), is becoming a useful method to determine atomic-resolution structures of proteins from micrometer-sized crystals with bright X-ray sources. Because of unknown orientations of crystals in SX, indexing ambiguity issue arises when the symmetry of Bravais lattice is higher than the space group symmetry, making some diffraction signals wrongly merged to the total intensity in twinned orientations. In this research, we developed a program within the CrystFEL framework, the EM-detwin, to resolve this indexing ambiguity problem based on the expectation-maximization algorithm. Testing results on the performance of the EM-detwin have demonstrated its usefulness in correctly indexing diffraction data as a valuable tool for SX data analysis.

Non-Nucleoside Reverse Transcriptase Inhibitors Join Forces with Integrase Inhibitors to Combat HIV

In the treatment of acquired immune deficiency syndrome (AIDS), the diarylpyrimidine (DAPY) analogs etravirine (ETR) and rilpivirine (RPV) have been widely effective against human immunodeficiency virus (HIV) variants that are resistant to other non-nucleoside reverse transcriptase inhibitors (NNRTIs). With non-inferior or improved efficacy, better safety profiles, and lower doses or pill burdens than other NNRTIs in the clinic, combination therapies including either of these two drugs have led to higher adherence than other NNRTI-containing treatments. In a separate development, HIV integrase strand transfer inhibitors (INSTIs) have shown efficacy in treating AIDS, including raltegravir (RAL), elvitegravir (EVG), cabotegravir (CAB), bictegravir (BIC), and dolutegravir (DTG). Of these, DTG and BIC perform better against a wide range of resistance mutations than other INSTIs. Nevertheless, drug-resistant combinations of mutations have begun to emerge against all DAPYs and INSTIs, attributable in part to non-adherence. New dual therapies that may promote better adherence combine ETR or RPV with an INSTI and have been safer and non-inferior to more traditional triple-drug treatments. Long-acting dual- and triple-therapies combining ETR or RPV with INSTIs are under study and may further improve adherence. Here, highly resistant emergent mutations and efficacy data on these novel treatments are reviewed. Overall, ETR or RPV, in combination with INSTIs, may be treatments of choice as long-term maintenance therapies that optimize efficacy, adherence, and safety.

The XFEL Protein Crystallography: Developments and Perspectives

In the past 10 years, the world has witnessed the revolutionary development of X-ray free electron lasers (XFELs) and their applications in many scientific disciplinaries [...].