Improvements to the APBS biomolecular solvation software suite

The Adaptive Poisson-Boltzmann Solver (APBS) software was developed to solve the equations of continuum electrostatics for large biomolecular assemblages that has provided impact in the study of a broad range of chemical, biological, and biomedical applications. APBS addresses three key technology challenges for understanding solvation and electrostatics in biomedical applications: accurate and efficient models for biomolecular solvation and electrostatics, robust and scalable software for applying those theories to biomolecular systems, and mechanisms for sharing and analyzing biomolecular electrostatics data in the scientific community. To address new research applications and advancing computational capabilities, we have continually updated APBS and its suite of accompanying software since its release in 2001. In this manuscript, we discuss the models and capabilities that have recently been implemented within the APBS software package including: a Poisson-Boltzmann analytical and a semi-analytical solver, an optimized boundary element solver, a geometry-based geometric flow solvation model, a graph theory based algorithm for determining p$K_a$ values, and an improved web-based visualization tool for viewing electrostatics

Identifying prospective inhibitors against LdtMt5 from Mycobacterium tuberculosis as a potential drug target.

Masters Degree. University of KwaZulu-Natal, Durban.Tuberculosis (TB) caused by the bacterium, Mycobacterium tuberculosis (M.tb) has resulted in an unprecedented number of deaths over centuries. L,D-transpeptidase enzymes are known to play a crucial role in the biosynthesis of the cell wall, which confers resistance to most antibiotics. These enzymes catalyze the 3→3 peptidoglycan cross-links of the M.tb cell wall. Specific β-lactam antibiotics (carbapenems) have been reported to inhibit cell wall polymerization of M.tb and they inactivate L,D-transpeptidases through acylation. L,Dtranspeptidase 5 (LdtMt5) is a unique paralog and a vital protein in maintaining integrity of the cell wall specifically in peptidoglycan metabolism therefore making it an important protein target. Carbapenems inhibit LdtMt2, but do not show reasonable inhibitory activities against LdtMt5. We therefore sought to perform virtual screening in order to acquire potential inhibitors against LdtMt5 and to investigate the affinity and to calculate the binding free energies between LdtMt5 and potential inhibitors. Furthermore, we sought to investigate the nature of the transition state involved in the catalytic reaction mechanism; to determine the activation free energies of the mechanism using ONIOM through the thermodynamics and energetics of the reaction path and lastly to express, purify and perform inhibition studies on LdtMt5. A total of 12766 compounds were computationally screened from the ZINC database to identify potential leads against LdtMt5. Docking was performed using two different software programs. Molecular dynamics (MD) simulations were subsequently performed on compounds obtained through virtual screening. Density functional theory (DFT) calculations were then carried out to understand the catalytic mechanism of LdtMt5 with respect to β-lactam derivatives using a hybrid ONIOM quantum mechanics/molecular mechanics (QM/MM) method. LdtMt5 complexes with six selected β-lactam compounds were evaluated. Finally, a lyophilised pET28a-LdtMt5 was used to transform E. coli strain BL21 (DE3) and SDS-PAGE was used to verify the purity, molecular weight and protein profile determination. Finally, an in vitro binding thermodynamics analysis using isothermal titration calorimetry (ITC) was later on performed on a single compound (the strongest binder) from the final set, in a bid to further validate the calculated binding energy values. A number of compounds from four different antimicrobial classes (n = 98) were obtained from the virtual screening and those with docking scores ranging from -7.2 to -9.9 kcal mol-1 were considered for MD analysis (n = 37). A final set of 10 compounds which exhibited the greatest affinity, from four antibiotic classes was selected and Molecular Mechanics/Generalized Born iii Surface Area (MM-GBSA) binding free energies (ΔGbind) from the set were characterised. The calculated binding free energies ranged from -30.68 to -48.52 kcal mol-1 . The β-lactam class of compounds demonstrated the highest ΔGbind and also the greatest number of potential inhibitors. The DFT activation energies (∆G # ) obtained for the acylation of LdtMt5 by the six selected β-lactams were calculated as 13.67, 20.90, 22.88, 24.29, 27.86 and 28.26 kcal mol-1 . The ∆G# results from the 6-membered ring transition state (TS) revealed that all selected six βlactams were thermodynamically more favourable than previously calculated activation energy values for imipenem and meropenem complexed with LdtMt5. The results are also comparable to those observed for LdtMt2, however for compound 1 the values are considerably lower than those obtained for meropenem and imipenem in complex with LdtMt2, thus suggesting in theory that compound 1 is a more potent inhibitor of LdtMt5. We also report the successful expression and and purification of LdtMt5, however the molecule selected for the in vitro inhibition study gave a poor result. On further review, we concluded that the main cause of this outcome was due to the relatively low insolubility of the compound. The outcome of this study provides insight into the design of potential novel leads for LdtMt5. Our screening obtained ten novel compounds from four different antimicrobial classes. We suggest that further in vitro binding thermodynamics analysis of the novel compounds from the four classes, including the carbapenems be performed to evaluate inhibition of these compounds on LdtMt5. If the experimental observations suggest binding affinity to the protein, catalytic mechanistic studies can be undertaken. These results will also be used to verify or modify our computational model

Physics-based visual characterization of molecular interaction forces

Molecular simulations are used in many areas of biotechnology, such as drug design and enzyme engineering. Despite the development of automatic computational protocols, analysis of molecular interactions is still a major aspect where human comprehension and intuition are key to accelerate, analyze, and propose modifications to the molecule of interest. Most visualization algorithms help the users by providing an accurate depiction of the spatial arrangement: the atoms involved in inter-molecular contacts. There are few tools that provide visual information on the forces governing molecular docking. However, these tools, commonly restricted to close interaction between atoms, do not consider whole simulation paths, long-range distances and, importantly, do not provide visual cues for a quick and intuitive comprehension of the energy functions (modeling intermolecular interactions) involved. In this paper, we propose visualizations designed to enable the characterization of interaction forces by taking into account several relevant variables such as molecule-ligand distance and the energy function, which is essential to understand binding affinities. We put emphasis on mapping molecular docking paths obtained from Molecular Dynamics or Monte Carlo simulations, and provide time-dependent visualizations for different energy components and particle resolutions: atoms, groups or residues. The presented visualizations have the potential to support domain experts in a more efficient drug or enzyme design process.Peer ReviewedPostprint (author's final draft

Molecular Modeling and Experimental Studies on Ligand Recognition in the LPA5 G Protein-Coupled Receptor

Lysophosphatidic acid (LPA) is a phospholipid growth factor mediating numerous biological effects such as platelet aggregation, mast cell activation, cell differentiation, cell migration, and cell survival by acting on specific LPA G protein-coupled receptors. Currently there are nine LPA receptors identified in the literature, LPA1-9. LPA1-3 are members of the endothelial differentiation gene (EDG) family and share approximately 50% sequence identity at the primary sequence level. LPA4-9 are structurally distinct from the EDG receptors with LPA5 sharing approximately 30% sequence identity with LPA4 at the primary sequence level. Due to the emerging role of LPA5 in human platelet activation, cancer, and neuropathic pain, a thorough characterization of LPA5is needed for the development of compounds to serve as starting points for anti-thrombotic and anti-cancer therapies as well as to inhibit neuropathic pain. In this dissertation we describe LPA5 pharmacophore model development and performance, LPA5 homology model evaluation and optimization through docking and site-directed mutagenesis studies, and structure-activity relationships (SAR) analysis at LPA5. Docking simulations were performed with the LPA5 homology model to computationally identify residues involved in ligand recognition. Pharmacophore modeling was performed to identify compounds with functional groups necessary for receptor inhibition to serve as starting points for therapeutic lead discovery. Our pharmacophore models identified weak partial antagonists and we validated headgroup recognition in alkyl-LPA (AGP 18:1), octadecenylthiophosphate (OTP 18:1), and oleyl-LPA (LPA 18:1). Specifically we proved three cationic residues to be involved in headgroup recongition: R78 (R2.60), R261 (R6.62), and R276 (R7.32). Furthermore we confirmed F71 (F2.53), F101 (F3.32), and M105 (M3.36) as three important residues involved in hydrophobic interactions with AGP, OTP, and LPA ligands. Also, we confirmed an alkyl-LPA preference in LPA5 relative to acyl-LPA. The SAR results suggests that the LPA5 binding pocket exhibits a bend that better accomadates cis relative to tran aslkenes located nine carbons from the headgroup, and that surrounding regions of the binding pocket are less bent, disfavoring recognition of ligands with cis double bonds located closer to or farther from the headgroup

Propofol inhibits the voltage-gated sodium channel NaChBac at multiple sites.

Voltage-gated sodium (NaV) channels are important targets of general anesthetics, including the intravenous anesthetic propofol. Electrophysiology studies on the prokaryotic NaV channel NaChBac have demonstrated that propofol promotes channel activation and accelerates activation-coupled inactivation, but the molecular mechanisms of these effects are unclear. Here, guided by computational docking and molecular dynamics simulations, we predict several propofol-binding sites in NaChBac. We then strategically place small fluorinated probes at these putative binding sites and experimentally quantify the interaction strengths with a fluorinated propofol analogue, 4-fluoropropofol. In vitro and in vivo measurements show that 4-fluoropropofol and propofol have similar effects on NaChBac function and nearly identical anesthetizing effects on tadpole mobility. Using quantitative analysis by 19F-NMR saturation transfer difference spectroscopy, we reveal strong intermolecular cross-relaxation rate constants between 4-fluoropropofol and four different regions of NaChBac, including the activation gate and selectivity filter in the pore, the voltage sensing domain, and the S4-S5 linker. Unlike volatile anesthetics, 4-fluoropropofol does not bind to the extracellular interface of the pore domain. Collectively, our results show that propofol inhibits NaChBac at multiple sites, likely with distinct modes of action. This study provides a molecular basis for understanding the net inhibitory action of propofol on NaV channels. © 2018 Wang et al

Insights into the structure and dynamics of lysyl oxidase propeptide, a flexible protein with numerous partners

Lysyl oxidase (LOX) catalyzes the oxidative deamination of lysine and hydroxylysine residues in collagens and elastin, which is the first step of the cross-linking of these extracellular matrix proteins. It is secreted as a proenzyme activated by bone morphogenetic protein-1, which releases the LOX catalytic domain and its bioactive N-terminal propeptide. We characterized the recombinant human propeptide by circular dichroism, dynamic light scattering, and small-angle X-ray scattering (SAXS), and showed that it is elongated, monomeric, disordered and flexible (Dmax: 11.7 nm, Rg: 3.7 nm). We generated 3D models of the propeptide by coarse-grained molecular dynamics simulations restrained by SAXS data, which were used for docking experiments. Furthermore, we have identified 17 new binding partners of the propeptide by label-free assays. They include four glycosaminoglycans (hyaluronan, chondroitin, dermatan and heparan sulfate), collagen I, cross-linking and proteolytic enzymes (lysyl oxidase-like 2, transglutaminase-2, matrix metalloproteinase-2), a proteoglycan (fibromodulin), one growth factor (Epidermal Growth Factor, EGF), and one membrane protein (tumor endothelial marker-8). This suggests new roles for the propeptide in EGF signaling pathway

Structure- and Ligand-Based Design of Novel Antimicrobial Agents

The use of computer based techniques in the design of novel therapeutic agents is a rapidly emerging field. Although the drug-design techniques utilized by Computational Medicinal Chemists vary greatly, they can roughly be classified into structure-based and ligand-based approaches. Structure-based methods utilize a solved structure of the design target, protein or DNA, usually obtained by X-ray or NMR methods to design or improve compounds with activity against the target. Ligand-based methods use active compounds with known affinity for a target that may yet be unresolved. These methods include Pharmacophore-based searching for novel active compounds or Quantitative Structure-Activity Relationship (QSAR) studies. The research presented here utilized both structure and ligand-based methods against two bacterial targets: Bacillus anthracis and Mycobacterium tuberculosis. The first part of this thesis details our efforts to design novel inhibitors of the enzyme dihydropteroate synthase from B. anthracis using crystal structures with known inhibitors bound. The second part describes a QSAR study that was performed using a series of novel nitrofuranyl compounds with known, whole-cell, inhibitory activity against M. tuberculosis. Dihydropteroate synthase (DHPS) catalyzes the addition of p-amino benzoic acid (pABA) to dihydropterin pyrophosphate (DHPP) to form pteroic acid as a key step in bacterial folate biosynthesis. It is the traditional target of the sulfonamide class of antibiotics. Unfortunately, bacterial resistance and adverse effects have limited the clinical utility of the sulfonamide antibiotics. Although six bacterial crystal structures are available, the flexible loop regions that enclose pABA during binding and contain key sulfonamide resistance sites have yet to be visualized in their functional conformation. To gain a new understanding of the structural basis of sulfonamide resistance, the molecular mechanism of DHPS action, and to generate a screening structure for high-throughput virtual screening, molecular dynamics simulations were applied to model the conformations of the unresolved loops in the active site. Several series of molecular dynamics simulations were designed and performed utilizing enzyme substrates and inhibitors, a transition state analog, and a pterin-sulfamethoxazole adduct. The positions of key mutation sites conserved across several bacterial species were closely monitored during these analyses. These residues were shown to interact closely with the sulfonamide binding site. The simulations helped us gain new understanding of the positions of the flexible loops during inhibitor binding that has allowed the development of a DHPS structural model that could be used for high-through put virtual screening (HTVS). Additionally, insights gained on the location and possible function of key mutation sites on the flexible loops will facilitate the design of new, potent inhibitors of DHPS that can bypass resistance mutations that render sulfonamides inactive. Prior to performing high-throughput virtual screening, the docking and scoring functions to be used were validated using established techniques against the B. anthracis DHPS target. In this validation study, five commonly used docking programs, FlexX, Surflex, Glide, GOLD, and DOCK, as well as nine scoring functions, were evaluated for their utility in virtual screening against the novel pterin binding site. Their performance in ligand docking and virtual screening against this target was examined by their ability to reproduce a known inhibitor conformation and to correctly detect known active compounds seeded into three separate decoy sets. Enrichment was demonstrated by calculated enrichment factors at 1% and Receiver Operating Characteristic (ROC) curves. The effectiveness of post-docking relaxation prior to rescoring and consensus scoring were also evaluated. Of the docking and scoring functions evaluated, Surflex with SurflexScore and Glide with GlideScore performed best overall for virtual screening against the DHPS target. The next phase of the DHPS structure-based drug design project involved high-throughput virtual screening against the DHPS structural model previously developed and docking methodology validated against this target. Two general virtual screening methods were employed. First, large, virtual libraries were pre-filtered by 3D pharmacophore and modified Rule-of-Three fragment constraints. Nearly 5 million compounds from the ZINC databases were screened generating 3,104 unique, fragment-like hits that were subsequently docked and ranked by score. Second, fragment docking without pharmacophore filtering was performed on almost 285,000 fragment-like compounds obtained from databases of commercial vendors. Hits from both virtual screens with high predicted affinity for the pterin binding pocket, as determined by docking score, were selected for in vitro testing. Activity and structure-activity relationship of the active fragment compounds have been developed. Several compounds with micromolar activity were identified and taken to crystallographic trials. Finally, in our ligand-based research into M. tuberculosis active agents, a series of nitrofuranylamide and related aromatic compounds displaying potent activity was investigated utilizing 3-Dimensional Quantitative Structure-Activity Relationship (3D-QSAR) techniques. Comparative Molecular Field Analysis (CoMFA) and Comparative Molecular Similarity Indices Analysis (CoMSIA) methods were used to produce 3D-QSAR models that correlated the Minimum Inhibitory Concentration (MIC) values against M. tuberculosis with the molecular structures of the active compounds. A training set of 95 active compounds was used to develop the models, which were then evaluated by a series of internal and external cross-validation techniques. A test set of 15 compounds was used for the external validation. Different alignment and ionization rules were investigated as well as the effect of global molecular descriptors including lipophilicity (cLogP, LogD), Polar Surface Area (PSA), and steric bulk (CMR), on model predictivity. Models with greater than 70% predictive ability, as determined by external validation and high internal validity (cross validated r2 \u3e .5) were developed. Incorporation of lipophilicity descriptors into the models had negligible effects on model predictivity. The models developed will be used to predict the activity of proposed new structures and advance the development of next generation nitrofuranyl and related nitroaromatic anti-tuberculosis agents