Benchmarking Adaptive Steered Molecular Dynamics (ASMD) on CHARMM Force Fields.

The potentials of mean force (PMFs) along the end-to-end distance of two different helical peptides have been obtained and benchmarked using the adaptive steered molecular dynamics (ASMD) method. The results depend strongly on the choice of force field driving the underlying all-atom molecular dynamics, and are reported with respect to the three most popular CHARMM force field versions: c22, c27 and c36. Two small peptides, ALA 10 and 1PEF, serve as the particular case studies. The comparisons between the versions of the CHARMM force fields provides both a qualitative and quantitative look at their performance in forced unfolding simulations in which peptides undergo large changes in structural conformations. We find that ASMD with the underlying c36 force field provides the most robust results for the selected benchmark peptides.

Identification of Zika Virus Inhibitors Using Homology Modeling and Similarity-Based Screening to Target Glycoprotein E.

The World Health Organization has designated Zika virus (ZIKV) as a dangerous, mosquito-borne pathogen that can cause severe developmental defects. The primary goal of this work was identification of small molecules as potential ZIKV inhibitors that target the viral envelope glycoprotein (ZIKV E) involved in membrane fusion and viral entry. A homology model of ZIKV E containing the small molecule ß-octyl glucoside (BOG) was constructed, on the basis of an analogous X-ray structure from dengue virus, and >4 million commercially available compounds were computationally screened using the program DOCK6. A key feature of the screen involved the use of similarity-based scoring to identify inhibitor candidates that make similar interaction energy patterns (molecular footprints) as the BOG reference. Fifty-three prioritized compounds underwent experimental testing using cytotoxicity, cell viability, and tissue culture infectious dose 50% (TCID50) assays. Encouragingly, relative to a known control (NITD008), six compounds were active in both the cell viability assay and the TCID50 infectivity assay, and they showed activity in a third caspase activity assay. In particular, compounds 8 and 15 (tested at 25 µM) and compound 43 (tested at 10 µM) appeared to provide significant protection to infected cells, indicative of anti-ZIKV activity. Overall, the study highlights how similarity-based scoring can be leveraged to computationally identify potential ZIKV E inhibitors that mimic a known reference (in this case BOG), and the experimentally verified hits provide a strong starting point for further refinement and optimization efforts.

Alchemical Binding Free Energy Calculations in AMBER20: Advances and Best Practices for Drug Discovery.

Predicting protein-ligand binding affinities and the associated thermodynamics of biomolecular recognition is a primary objective of structure-based drug design. Alchemical free energy simulations offer a highly accurate and computationally efficient route to achieving this goal. While the AMBER molecular dynamics package has successfully been used for alchemical free energy simulations in academic research groups for decades, widespread impact in industrial drug discovery settings has been minimal because of the previous limitations within the AMBER alchemical code, coupled with challenges in system setup and postprocessing workflows. Through a close academia-industry collaboration we have addressed many of the previous limitations with an aim to improve accuracy, efficiency, and robustness of alchemical binding free energy simulations in industrial drug discovery applications. Here, we highlight some of the recent advances in AMBER20 with a focus on alchemical binding free energy (BFE) calculations, which are less computationally intensive than alternative binding free energy methods where full binding/unbinding paths are explored. In addition to scientific and technical advances in AMBER20, we also describe the essential practical aspects associated with running relative alchemical BFE calculations, along with recommendations for best practices, highlighting the importance not only of the alchemical simulation code but also the auxiliary functionalities and expertise required to obtain accurate and reliable results. This work is intended to provide a contemporary overview of the scientific, technical, and practical issues associated with running relative BFE simulations in AMBER20, with a focus on real-world drug discovery applications.

Structure-based identification of inhibitors targeting obstruction of the HIVgp41 N-heptad repeat trimer.

The viral protein HIVgp41 is an attractive and validated drug target that proceeds through a sequence of conformational changes crucial for membrane fusion, which facilitates viral entry. Prior work has identified inhibitors that interfere with the formation of a required six-helix bundle, composed of trimeric C-heptad (CHR) and N-heptad (NHR) repeat elements, through blocking association of an outer CHR helix or obstructing formation of the inner NHR trimer itself. In this work, we employed similarity-based scoring to identify and experimentally characterize 113 compounds, related to 2 small-molecule inhibitors recently reported by Allen et al. (Bioorg. Med. Chem Lett.2015, 25 2853-59), proposed to act via the NHR trimer obstruction mechanism. The compounds were first tested in an HIV cell-cell fusion assay with the most promising evaluated in a second, more biologically relevant viral entry assay. Of the candidates, compound #11 emerged as the most promising hit (IC50=37.81µM), as a result of exhibiting activity in both assays with low cytotoxicity, as was similarly seen with the known control peptide inhibitor C34. The compound also showed no inhibition of VSV-G pseudotyped HIV entry compared to a control inhibitor suggesting it was specific for HIVgp41. Molecular dynamics simulations showed the predicted DOCK pose of #11 interacts with HIVgp41 in an energetic fashion (per-residue footprints) similar to the four native NHR residues (IQLT) which candidate inhibitors were intended to mimic.

Defective hydrophobic sliding mechanism and active site expansion in HIV-1 protease drug resistant variant Gly48Thr/Leu89Met: mechanisms for the loss of saquinavir binding potency.

HIV drug resistance continues to emerge; consequently, there is an urgent need to develop next generation antiretroviral therapeutics.1 Here we report on the structural and kinetic effects of an HIV protease drug resistant variant with the double mutations Gly48Thr and Leu89Met (PRG48T/L89M), without the stabilizing mutations Gln7Lys, Leu33Ile, and Leu63Ile. Kinetic analyses reveal that PRG48T/L89M and PRWT share nearly identical Michaelis-Menten parameters; however, PRG48T/L89M exhibits weaker binding for IDV (41-fold), SQV (18-fold), APV (15-fold), and NFV (9-fold) relative to PRWT. A 1.9 Å resolution crystal structure was solved for PRG48T/L89M bound with saquinavir (PRG48T/L89M-SQV) and compared to the crystal structure of PRWT bound with saquinavir (PRWT-SQV). PRG48T/L89M-SQV has an enlarged active site resulting in the loss of a hydrogen bond in the S3 subsite from Gly48 to P3 of SQV, as well as less favorable hydrophobic packing interactions between P1 Phe of SQV and the S1 subsite. PRG48T/L89M-SQV assumes a more open conformation relative to PRWT-SQV, as illustrated by the downward displacement of the fulcrum and elbows and weaker interatomic flap interactions. We also show that the Leu89Met mutation disrupts the hydrophobic sliding mechanism by causing a redistribution of van der Waals interactions in the hydrophobic core in PRG48T/L89M-SQV. Our mechanism for PRG48T/L89M-SQV drug resistance proposes that a defective hydrophobic sliding mechanism results in modified conformational dynamics of the protease. As a consequence, the protease is unable to achieve a fully closed conformation that results in an expanded active site and weaker inhibitor binding.

pH-REMD simulations indicate that the catalytic aspartates of HIV-1 protease exist primarily in a monoprotonated state.

The protonation state of the catalytic aspartates of HIV-1 protease (HIVPR) is atypical and as a result is the subject of much debate. Modeling of the correct protonation state of the aspartates is vital in computational drug design. Using pH replica-exchange molecular dynamics, we simulated the apo and bound forms of HIV-1 protease with 12 different protease inhibitors to investigate the pKa of not only the catalytic dyad but also the other titrating residues in HIVPR. The results obtained from these simulations are compared to experiment where possible. This study provides evidence that the catalytic aspartates are primarily in a monoprotonated state for both the apo and bound forms of HIVPR in the pH range where generally most experiments and computational simulations occur.

MMPBSA.py: An Efficient Program for End-State Free Energy Calculations.

MM-PBSA is a post-processing end-state method to calculate free energies of molecules in solution. MMPBSA.py is a program written in Python for streamlining end-state free energy calculations using ensembles derived from molecular dynamics (MD) or Monte Carlo (MC) simulations. Several implicit solvation models are available with MMPBSA.py, including the Poisson-Boltzmann Model, the Generalized Born Model, and the Reference Interaction Site Model. Vibrational frequencies may be calculated using normal mode or quasi-harmonic analysis to approximate the solute entropy. Specific interactions can also be dissected using free energy decomposition or alanine scanning. A parallel implementation significantly speeds up the calculation by dividing frames evenly across available processors. MMPBSA.py is an efficient, user-friendly program with the flexibility to accommodate the needs of users performing end-state free energy calculations. The source code can be downloaded at http://ambermd.org/ with AmberTools, released under the GNU General Public License.

Preliminary molecular dynamic simulations of the estrogen receptor alpha ligand binding domain from antagonist to apo.

Estrogen receptors (ER) are known as nuclear receptors. They exist in the cytoplasm of human cells and serves as a DNA binding transcription factor that regulates gene expression. However the estrogen receptor also has additional functions independent of DNA binding. The human estrogen receptor comes in two forms, alpha and beta. This work focuses on the alpha form of the estrogen receptor. The ERalpha is found in breast cancer cells, ovarian stroma cells, endometrium, and the hypothalamus. It has been suggested that exposure to DDE, a metabolite of DDT, and other pesticides causes conformational changes in the estrogen receptor. Before examining these factors, this work examines the protein unfolding from the antagonist form found in the 3ERT PDB crystal structure. The 3ERT PDB crystal structure has the estrogen receptor bound to the cancer drug 4-hydroxytamoxifen. The 4-hydroxytamoxifen ligand was extracted before the simulation, resulting in new conformational freedom due to absence of van der Waals contacts between the ligand and the receptor. The conformational changes that result expose the binding clef of the co peptide beside Helix 12 of the receptor forming an apo conformation. Two key conformations in the loops at either end of the H12 are produced resulting in the antagonist to apo conformation transformation. The results were produced over a 42ns Molecular Dynamics simulation using the AMBER FF99SB force field.