Dynamozones are the most obvious sign of the evolution of conformational dynamics in HIV-1 protease

A review on description dynamics and conformational changes of proteins using combination of principal component analysis and molecular dynamics simulation

Understanding how proteins behave dynamically and undergo conformational changes is essential to comprehending their biological roles. This review article examines the potent tool of using Molecular Dynamics simulations in conjunction with Principal Component Analysis (PCA) to explore protein dynamics. Molecular dynamics data can be made easier to read by removing prominent patterns through the use of PCA, a sophisticated dimensionality reduction approach. Researchers can obtain critical insights into the fundamental principles governing protein function by using PCA on MD simulation data. We provide a systematic approach to PCA that includes data collection, input coordinate selection, and result interpretation. Protein collective movements and fundamental dynamics are made visible by PCA, which makes it possible to identify conformational substates that are crucial to function. By means of principal component analysis, scientists are able to observe and measure large-scale movements, like hinge bending and domain motions, as well as pinpoint areas of protein structural stiffness and flexibility. Moreover, PCA allows temporal separation, distinguishing slower global motions from faster local changes. A strong foundation for researching protein dynamics is provided by the combination of PCA and Molecular Dynamics simulations, which have applications in drug development and enhance our comprehension of intricate biological systems.

Comparative study of stability and activity of wild-type and mutant human carbonic anhydrase II enzymes using molecular dynamics and docking simulations

The human carbonic anhydrase II (HCA II) enzyme is a cytosolic protein located in the membrane of red blood cells that reversible hydration of carbon dioxide (CO2). Considering the critical role of the HCA II and the effects of some mutations on the activity and stability of the enzyme in humans, several computational methods are used to study the structure and dynamics of the wild-type and the mutant enzymes with three ligands, CO2, 4-nitrophenyl acetate and acetazolamide. Our results of MD simulation of a wild-type enzyme with 4-nitrophenyl acetate show that it created essential effects on the fluctuation of this enzyme and made it more unstable and less compact than the same enzyme without ligand. In the MD of the mutant enzyme with 4-nitrophenyl acetate ligand, no significant difference is observed between with and without ligand. The affinity of the wild-type enzyme to the 4-nitrophenyl acetate is notably higher than the mutant enzyme with the same ligand. Furthermore, results showed that wild-type and mutant enzymes with CO2 are more favorable in stability and flexibility than the same enzymes without ligand. The MD results of wild-type with acetazolamide indicate instability compare without ligand, but in MD of mutant enzyme with acetazolamide show that it more stable and compact than the same enzyme without ligand. Finally, Comparing protein trajectories to assess the impact of ligands on the stability and activity of HCA II enzymes can have medical applications and can in the engineering and design of new variants of carbonic anhydrase enzyme.

Discovery of novel MLK4 inhibitors against colorectal cancer through computational approaches

Colorectal cancer (CRC) is a significant health issue globally, affecting approximately 10 % of the world's population. The prevalence of CRC highlights the need for effective treatments and prevention strategies. The current therapeutic option, such as chemotherapy, has significant side effects. Thus, this study investigated the anticancer properties of Sanguinarine derivatives, an alkaloid found in traditional herbs via chemoinformatic approaches. Six Sanguinarine derivatives were discovered through virtual screening and molecular docking to determine their binding affinities against the mixed lineage kinase (MLK4) protein which is responsible for CRC. All the compounds were found to be more effective than standard drug used for colorectal cancer treatment, with Sanguinarine derivative 11 showing the highest affinity. The stability of the drug was confirmed through molecular dynamics simulations at 500 ns. This suggests that compound 11 has a higher chance of replacing 5-Fluorouracil, which is currently a widely used chemotherapy drug. Before molecular dynamics simulations, the pharmacokinetic and chemical properties of Sanguinarine derivatives were determined using pkCSM server and DFT method, respectively. The results support that compound 11 is a good drug candidate, as evidenced by Lipinski's Rule of Five. Therefore, compound 11 is recommended for further analysis via in vivo and in vitro studies to confirm its efficacy and safety.

Alisol C 23-acetate might be a lead compound of potential lipase inhibitor from Alismatis Rhizoma: Screening, identification and molecular dynamics simulation

Alismatis Rhizoma (AR), a traditional Chinese medicine for treating obesity in traditional Chinese medicine clinic, is recognized as a promising source of lead compounds of lipase inhibitors. Ultrafiltration centrifugal combined with liquid chromatography-mass spectrometry (UF-LC-MS) was used for screening potential lipase inhibitors from AR, and the result indicated the binding capacity between compound 7 and lipase (92.3 ± 1.28 %) was significantly higher than other triterpenoids, and was identified as alisol C 23-acetate. It exhibited a mixed-type inhibitory behavior with an IC50 value of 84.88 ± 1.03 μM. Subsequently, the binding pockets of alisol C 23-acetate to lipase were predicted, and their binding mechanism was explored with molecular simulation. Pocket 1 (active center) and pocket 4 might be the orthosteric and allosteric binding sites of alisol C 23-acetate to lipase, respectively. The interaction between alisol C 23-acetate and lipase was identified to involve key amino acid residues such as GLY-77, PHE-78, TYR-115, LEU-154, PRO-181, PHE-216, LEU-264, ASP-278, GLN-306, ARG-313, and VAL-426. Meanwhile, alisol C 23-acetate remained stable during the intestinal digestive but degraded in the gastric digestion. Overall, alisol C 23-acetate is expected to be the lead compound of lipase inhibitors for treating obesity.

Associating protein sequence positions with the modulation of quantitative phenotypes

Although protein sequences encode the information for folding and function, understanding their link is not an easy task. Unluckily, the prediction of how specific amino acids contribute to these features is still considerably impaired. Here, we developed a simple algorithm that finds positions in a protein sequence with potential to modulate the studied quantitative phenotypes. From a few hundred protein sequences, we perform multiple sequence alignments, obtain the per-position pairwise differences for both the sequence and the observed phenotypes, and calculate the correlation between these last two quantities. We tested our methodology with four cases: archaeal Adenylate Kinases and the organisms optimal growth temperatures, microbial rhodopsins and their maximal absorption wavelengths, mammalian myoglobins and their muscular concentration, and inhibition of HIV protease clinical isolates by two different molecules. We found from 3 to 10 positions tightly associated with those phenotypes, depending on the studied case. We showed that these correlations appear using individual positions but an improvement is achieved when the most correlated positions are jointly analyzed. Noteworthy, we performed phenotype predictions using a simple linear model that links per-position divergences and differences in the observed phenotypes. Predictions are comparable to the state-of-art methodologies which, in most of the cases, are far more complex. All of the calculations are obtained at a very low information cost since the only input needed is a multiple sequence alignment of protein sequences with their associated quantitative phenotypes. The diversity of the explored systems makes our work a valuable tool to find sequence determinants of biological activity modulation and to predict various functional features for uncharacterized members of a protein family.

Natural Polymorphisms D60E and I62V Stabilize a Closed Conformation in HIV-1 Protease in the Absence of an Inhibitor or Substrate

HIV infection remains a global health issue plagued by drug resistance and virological failure. Natural polymorphisms (NPs) contained within several African and Brazilian protease (PR) variants have been shown to induce a conformational landscape of more closed conformations compared to the sequence of subtype B prevalent in North America and Western Europe. Here we demonstrate through experimental pulsed EPR distance measurements and molecular dynamic (MD) simulations that the two common NPs D60E and I62V found within subtypes F and H can induce a closed conformation when introduced into HIV-1PR subtype B. Specifically, D60E alters the conformation in subtype B through the formation of a salt bridge with residue K43 contained within the nexus between the flap and hinge region of the HIV-1 PR fold. On the other hand, I62V modulates the packing of the hydrophobic cluster of the cantilever and fulcrum, also resulting in a more closed conformation.