How Good is Jarzynski's Equality for Computer-Aided Drug Design?
ABSTRACT: Accurate determination of the binding affinity of the ligand to the receptor remains a difficult problem in computer-aided drug design. Here, we study and compare the efficiency of Jarzynski's equality (JE) combined with steered molecular dynamics and the linear interaction energy (LIE) method by assessing the binding affinity of 23 small compounds to six receptors, including ?-lactamase, thrombin, factor Xa, HIV-1 protease (HIV), myeloid cell leukemia-1, and cyclin-dependent kinase 2 proteins. It was shown that Jarzynski's nonequilibrium binding free energy ?GneqJar correlates with the available experimental data with the correlation levels R = 0.89, 0.86, 0.83, 0.80, 0.83, and 0.81 for six data sets, while for the binding free energy ?GLIE obtained by the LIE method, we have R = 0.73, 0.80, 0.42, 0.23, 0.85, and 0.01. Therefore, JE is recommended to be used for ranking binding affinities as it provides accurate and robust results. In contrast, LIE is not as reliable as JE, and it should be used with caution, especially when it comes to new systems.
Project description:Indirect (S)QM/MM free energy simulations (FES) are vital to efficiently incorporating sufficient sampling and accurate (QM) energetic evaluations when estimating free energies of practical/experimental interest. Connecting between levels of theory, i.e., calculating ? A l o w ? h i g h , remains to be the most challenging step within an indirect FES protocol. To improve calculations of ? A l o w ? h i g h , we must: (1) compare the performance of all FES methods currently available; and (2) compile and maintain datasets of ? A l o w ? h i g h calculated for a wide-variety of molecules so that future practitioners may replicate or improve upon the current state-of-the-art. Towards these two aims, we introduce a new dataset, "HiPen", which tabulates ? A g a s M M ? 3 o b (the free energy associated with switching from an M M to an S C C - D F T B molecular description using the 3ob parameter set in gas phase), calculated for 22 drug-like small molecules. We compare the calculation of this value using free energy perturbation, Bennett's acceptance ratio, Jarzynski's equation, and Crooks' equation. We also predict the reliability of each calculated ? A g a s M M ? 3 o b by evaluating several convergence criteria including sample size hysteresis, overlap statistics, and bias metric ( ? ). Within the total dataset, three distinct categories of molecules emerge: the "good" molecules, for which we can obtain converged ? A g a s M M ? 3 o b using Jarzynski's equation; "bad" molecules which require Crooks' equation to obtain a converged ? A g a s M M ? 3 o b ; and "ugly" molecules for which we cannot obtain reliably converged ? A g a s M M ? 3 o b with either Jarzynski's or Crooks' equations. We discuss, in depth, results from several example molecules in each of these categories and describe how dihedral discrepancies between levels of theory cause convergence failures even for these gas phase free energy simulations.
Project description:Binding free energy (?Gbind) computation can play an important role in prioritizing compounds to be evaluated experimentally on their affinity for target proteins, yet fast and accurate ?Gbind calculation remains an elusive task. In this study, we compare the performance of two popular end-point methods, i.e., linear interaction energy (LIE) and molecular mechanics/Poisson-Boltzmann surface area (MM/PBSA), with respect to their ability to correlate calculated binding affinities of 27 thieno[3,2-d]pyrimidine-6-carboxamide-derived sirtuin 1 (SIRT1) inhibitors with experimental data. Compared with the standard single-trajectory setup of MM/PBSA, our study elucidates that LIE allows to obtain direct ("absolute") values for SIRT1 binding free energies with lower compute requirements, while the accuracy in calculating relative values for ?Gbind is comparable (Pearson's r = 0.72 and 0.64 for LIE and MM/PBSA, respectively). We also investigate the potential of combining multiple docking poses in iterative LIE models and find that Boltzmann-like weighting of outcomes of simulations starting from different poses can retrieve appropriate binding orientations. In addition, we find that in this particular case study the LIE and MM/PBSA models can be optimized by neglecting the contributions from electrostatic and polar interactions to the ?Gbind calculations.
Project description:We designed, synthesized, and identified JE-2147, an allophenylnorstatine-containing dipeptide HIV protease inhibitor (PI), which is potent against a wide spectrum of HIV-1, HIV-2, simian immunodeficiency virus, and various clinical HIV-1 strains in vitro. Drug-resistant clinical HIV-1 strains, isolated from seven patients who had failed 9-11 different anti-HIV therapeutics after 32-83 months, had a variety of drug-resistance-related amino acid substitutions and were highly and invariably resistant to all of the currently available anti-HIV agents. JE-2147 was, however, extremely potent against all such drug-resistant strains, with IC(50) values ranging from 13-41 nM (<2-fold changes in IC(50) compared with that of wild-type HIV-1). The emergence of JE-2147-resistant HIV-1 variants in vitro was substantially delayed compared with that of HIV-1 resistant to another allophenylnorstatine-containing compound, KNI-272, and other related PIs. Structural analysis revealed that the presence of a flexible P2' moiety is important for the potency of JE-2147 toward wild-type and mutant viruses. These data suggest that the use of flexible components may open a new avenue for designing PIs that resist the emergence of PI-resistant HIV-1. Further development of JE-2147 for treating patients harboring multi-PI-resistant HIV-1 is warranted.
Project description:Evidence indicated that socio-environmental factors were associated with occurrence of Japanese encephalitis (JE). This study explored the association of climate and socioeconomic factors with JE (2006-2014) in Shaanxi, China. JE data at the county level in Shaanxi were supplied by Shaanxi Center for Disease Control and Prevention. Population and socioeconomic data were obtained from the China Population Census in 2010 and statistical yearbooks. Meteorological data were acquired from the China Meteorological Administration. A Bayesian conditional autoregressive model was used to examine the association of meteorological and socioeconomic factors with JE. A total of 1197 JE cases were included in this study. Urbanization rate was inversely associated with JE incidence during the whole study period. Meteorological variables were significantly associated with JE incidence between 2012 and 2014. The excessive precipitation at lag of 1-2 months in the north of Shaanxi in June 2013 had an impact on the increase of local JE incidence. The spatial residual variations indicated that the whole study area had more stable risk (0.80-1.19 across all the counties) between 2012 and 2014 than earlier years. Public health interventions need to be implemented to reduce JE incidence, especially in rural areas and after extreme weather.
Project description:Japanese encephalitis (JE) is the leading cause of viral encephalitis in Asia. Acute encephalitis syndrome (AES) is a group of central nervous system (CNS) disorders caused by a wide range of viruses, bacteria, fungi, chemicals and toxins. It is important to distinguish between various forms of infectious encephalitis with similar clinical manifestations in order to ensure specific and accurate diagnosis and development of subsequent therapeutic strategies. Cerebrospinal fluid (CSF) is in direct contact with the CNS and hence it is considered to be an excellent source for identifying biomarkers for various neurological disorders. With the recent advancement in proteomic methodologies, the field of biomarker research has received a remarkable boost. The present study identifies potential biomarkers for JE using a proteomics based approach. The CSF proteomes from ten patients each with JE and Non-JE acute encephalitis were analyzed by 2D gel electrophoresis followed by mass spectrometry. Vitamin D-binding protein (DBP), fibrinogen gamma chain, fibrinogen beta chain, complement C4-B, complement C3 and cytoplasmic actin were found to be significantly elevated in case of JE indicating severe disruption of the blood brain barrier and DBP can be suggested to be an important diagnostic marker.
Project description:Computational protein binding affinity prediction can play an important role in drug research but performing efficient and accurate binding free energy calculations is still challenging. In the context of phase 2 of the Drug Design Data Resource (D3R) Grand Challenge 2 we used our automated eTOX ALLIES approach to apply the (iterative) linear interaction energy (LIE) method and we evaluated its performance in predicting binding affinities for farnesoid X receptor (FXR) agonists. Efficiency was obtained by our pre-calibrated LIE models and molecular dynamics (MD) simulations at the nanosecond scale, while predictive accuracy was obtained for a small subset of compounds. Using our recently introduced reliability estimation metrics, we could classify predictions with higher confidence by featuring an applicability domain (AD) analysis in combination with protein-ligand interaction profiling. The outcomes of and agreement between our AD and interaction-profile analyses to distinguish and rationalize the performance of our predictions highlighted the relevance of sufficiently exploring protein-ligand interactions during training and it demonstrated the possibility to quantitatively and efficiently evaluate if this is achieved by using simulation data only.
Project description:Calculating free energies of binding (?Gbind) between ligands and their target protein is of major interest to drug discovery and safety, yet it is still associated with several challenges and difficulties. Linear interaction energy (LIE) is an efficient in silico method for ?Gbind computation. LIE models can be trained and used to directly calculate binding affinities from interaction energies involving ligands in the bound and unbound states only, and LIE can be combined with statistical weighting to calculate ?Gbind for flexible proteins that may bind their ligands in multiple orientations. Here, we investigate if LIE predictions can be effectively improved by explicitly including the entropy of (de)solvation into our free-energy calculations. For that purpose, we combine LIE calculations for the protein-ligand-bound state with explicit free-energy perturbation to rigorously compute the unbound ligand's solvation free energy. We show that for 28 Cytochrome P450 2A6 (CYP2A6) ligands, coupling LIE with alchemical solvation free-energy calculation helps to improve obtained correlation between computed and reference (experimental) binding data.
Project description:Calculating the absolute binding free energies is a challenging task. Reliable estimates of binding free energies should provide a guide for rational drug design. It should also provide us with deeper understanding of the correlation between protein structure and its function. Further applications may include identifying novel molecular scaffolds and optimizing lead compounds in computer-aided drug design. Available options to evaluate the absolute binding free energies range from the rigorous but expensive free energy perturbation to the microscopic linear response approximation (LRA/beta version) and related approaches including the linear interaction energy (LIE) to the more approximated and considerably faster scaled protein dipoles Langevin dipoles (PDLD/S-LRA version) as well as the less rigorous molecular mechanics Poisson-Boltzmann/surface area (MM/PBSA) and generalized born/surface area (MM/GBSA) to the less accurate scoring functions. There is a need for an assessment of the performance of different approaches in terms of computer time and reliability. We present a comparative study of the LRA/beta, the LIE, the PDLD/S-LRA/beta, and the more widely used MM/PBSA and assess their abilities to estimate the absolute binding energies. The LRA and LIE methods perform reasonably well but require specialized parameterization for the nonelectrostatic term. The PDLD/S-LRA/beta performs effectively without the need of reparameterization. Our assessment of the MM/PBSA is less optimistic. This approach appears to provide erroneous estimates of the absolute binding energies because of its incorrect entropies and the problematic treatment of electrostatic energies. Overall, the PDLD/S-LRA/beta appears to offer an appealing option for the final stages of massive screening approaches.
Project description:Understanding the enzymatic mechanism that cellulases employ to degrade cellulose is critical to efforts to efficiently utilize plant biomass as a sustainable energy resource. A key component of cellulase action on cellulose is product inhibition from monosaccharide and disaccharides in the product site of cellulase tunnel. The absolute binding free energy of cellobiose and glucose to the product site of the catalytic tunnel of the Family 7 cellobiohydrolase (Cel7A) of Trichoderma reesei (Hypocrea jecorina) was calculated using two different approaches: steered molecular dynamics (SMD) simulations and alchemical free energy perturbation molecular dynamics (FEP/MD) simulations. For the SMD approach, three methods based on Jarzynski's equality were used to construct the potential of mean force from multiple pulling trajectories. The calculated binding free energies, -14.4 kcal/mol using SMD and -11.2 kcal/mol using FEP/MD, are in good qualitative agreement. Analysis of the SMD pulling trajectories suggests that several protein residues (Arg-251, Asp-259, Asp-262, Trp-376, and Tyr-381) play key roles in cellobiose and glucose binding to the catalytic tunnel. Five mutations (R251A, D259A, D262A, W376A, and Y381A) were made computationally to measure the changes in free energy during the product expulsion process. The absolute binding free energies of cellobiose to the catalytic tunnel of these five mutants are -13.1, -6.0, -11.5, -7.5, and -8.8 kcal/mol, respectively. The results demonstrated that all of the mutants tested can lower the binding free energy of cellobiose, which provides potential applications in engineering the enzyme to accelerate the product expulsion process and improve the efficiency of biomass conversion.
Project description:CCR5 is a CC chemokine receptor involved in the migration of effector leukocytes including macrophages, NK, and T cells into inflamed tissues. Also, the role of CCR5 in CD4(+)Foxp3(+) regulatory T cell (Treg) homing has recently begun to grab attention. Japanese encephalitis (JE) is defined as severe neuroinflammation of the central nervous system (CNS) following infection with mosquito-borne flavivirus JE virus. However, the potential contribution of CCR5 to JE progression via mediating CD4(+)Foxp3(+) Treg homing has not been investigated.Infected wild-type (Ccr5(+/+)) and CCR5-deficient (Ccr5(-/-)) mice were examined daily for mortality and clinical signs, and neuroinflammation in the CNS was evaluated by infiltration of inflammatory leukocytes and cytokine expression. In addition, viral burden, NK- and JEV-specific T cell responses were analyzed. Adoptive transfer of CCR5(+)CD4(+)Foxp3(+) Tregs was used to evaluate the role of Tregs in JE progression.CCR5 ablation exacerbated JE without altering viral burden in the extraneural and CNS tissues, as manifested by increased CNS infiltration of Ly-6C(hi) monocytes and Ly-6G(hi) granulocytes. Compared to Ccr5(+/+) mice, Ccr5(-/-) mice unexpectedly showed increased responses of IFN-?(+)NK and CD8(+) T cells in the spleen, but not CD4(+) T cells. More interestingly, CCR5-ablation resulted in a skewed response to IL-17(+)CD4(+) Th17 cells and correspondingly reduced CD4(+)Foxp3(+) Tregs in the spleen and brain, which was closely associated with exacerbated JE. Our results also revealed that adoptive transfer of sorted CCR5(+)CD4(+)Foxp3(+) Tregs into Ccr5(-/-) mice could ameliorate JE progression without apparently altering the viral burden and CNS infiltration of IL-17(+)CD4(+) Th17 cells, myeloid-derived Ly-6C(hi) monocytes and Ly-6G(hi) granulocytes. Instead, adoptive transfer of CCR5(+)CD4(+)Foxp3(+) Tregs into Ccr5(-/-) mice resulted in increased expression of anti-inflammatory cytokines (IL-10 and TGF-?) in the spleen and brain, and transferred CCR5(+) Tregs were found to produce IL-10.CCR5 regulates JE progression via governing timely and appropriate CNS infiltration of CD4(+)Foxp3(+) Tregs, thereby facilitating host survival. Therefore, this critical and extended role of CCR5 in JE raises possible safety concerns regarding the use of CCR5 antagonists in human immunodeficiency virus (HIV)-infected individuals who inhabit regions in which both HIV and flaviviruses, such as JEV and West Nile virus, are endemic.