We incorporate the Poisson–Boltzmann
(PB) theory of electrostatics
into our variational implicit-solvent model (VISM) for the solvation
of charged molecules in an aqueous solvent. In order to numerically
relax the VISM free-energy functional by our level-set method, we
develop highly accurate methods for solving the dielectric PB equation
and for computing the dielectric boundary force. We also apply our
VISM-PB theory to analyze the solvent potentials of mean force and
the effect of charges on the hydrophobic hydration for some selected
molecular systems. These include some single ions, two charged particles,
two charged plates, and the host–guest system Cucurbituril
and Bicyclo[2.2.2]octane. Our computational results show that VISM
with PB theory can capture well the sensitive response of capillary
evaporation to the charge in hydrophobic confinement and the polymodal
hydration behavior and can provide accurate estimates of binding affinity
of the host–guest system. We finally discuss several issues
for further improvement of VISM.
The flavoenzyme UDP-galactopyranose mutase (UGM) is a key enzyme in galactofuranose biosynthesis. The enzyme catalyzes the 6-to-5 ring contraction of UDP-galactopyranose to UDP-galactofuranose. Galactofuranose is absent in humans yet is an essential component of bacterial and fungal cell walls and a cell surface virulence factor in protozoan parasites. Thus, inhibition of galactofuranose biosynthesis is a valid strategy for developing new antimicrobials. UGM is an excellent target in this effort because the product of the UGM reaction represents the first appearance of galactofuranose in the biosynthetic pathway. The UGM reaction is redox neutral, which is atypical for flavoenzymes, motivating intense examination of the chemical mechanism and structural features that tune the flavin for its unique role in catalysis. These studies show that the flavin functions as nucleophile, forming a flavin-sugar adduct that facilitates galactose-ring opening and contraction. The 3-dimensional fold is novel and conserved among all UGMs, however the larger eukaryotic enzymes have additional secondary structure elements that lead to significant differences in quaternary structure, substrate conformation, and conformational flexibility. Here we present a comprehensive review of UGM three-dimensional structure, provide an update on recent developments in understanding the mechanism of the enzyme, and summarize computational studies of active site flexibility.
flavin-dependent reaction; galactofuranose; non-redox reaction; neglected diseases; tuberculosis; redox-switch; conformational changes; protein dynamics
A number of marine natural products are potent inhibitors of proteases, an important drug target class in human diseases. Hence, marine cyanobacterial extracts were assessed for inhibitory activity to human cathepsin L. Herein, we have shown that gallinamide A potently and selectively inhibits the human cysteine protease, cathepsin L. With 30 min of preincubation, gallinamide A displayed an IC50 of 5.0 nM, and kinetic analysis demonstrated an inhibition constant of ki = 9000 ± 260 M−1 s−1. Preincubation-dilution and activity-probe experiments revealed an irreversible mode of inhibition, and comparative IC50 values display a 28- to 320- fold greater selectivity toward cathepsin L than closely related human cysteine cathepsins V or B. Molecular docking and molecular dynamics simulations were used to determine the pose of gallinamide in the active site of cathepsin L. These data resulted in the identification of a pose characterized by high stability, a consistent hydrogen bond network, and the reactive Michael acceptor enamide of gallinamide A positioned near the active site cysteine of the protease, leading to a proposed mechanism of covalent inhibition. These data reveal and characterize the novel activity of gallinamide A as a potent inhibitor of human cathepsin L.
Staphylococcus aureus is the leading cause of hospital-acquired infections in the United States. The emergence of multi-drug resistant strains of S. aureus has created an urgent need for new antibiotics. S. aureus uses the sortase A (SrtA) enzyme to display surface virulence factors suggesting that compounds that inhibit its activity will function as potent anti-infective agents. Here we report the identification of several inhibitors of SrtA using virtual screening methods that employ the relaxed complex scheme, an advanced computer-docking methodology that accounts for protein receptor flexibility. Experimental testing validates that several compounds identified in the screen inhibit the activity of SrtA. A lead compound based on the 2-phenyl-2,3-dihydro-1H-perimidine scaffold is particularly promising and its binding mechanism was further investigated using molecular dynamics simulations and by conducting preliminary structure activity relationship studies.
Staphylococcus aureus; MRSA; sortase; SrtA; transpeptidation; Gram-positive; drug discovery; virtual screening; relaxed complex scheme; molecular dynamics; docking
An alchemical free energy method with explicit solvent molecular dynamics simulations was applied as part of the blind prediction contest SAMPL3 to calculate binding free energies for seven guests to an acyclic cucurbit-[n]uril host. The predictions included determination of protonation states for both host and guests, docking pose generation, and binding free energy calculations using thermodynamic integration. We found a root mean square error (RMSE) of 3.6 kcal mol−1 from the reference experimental results, with an R2 correlation of 0.51. The agreement with experiment for the largest contributor to this error, guest 6, is improved by 1.7 kcal mol−1 when a periodicity-induced free energy correction is applied. The corrections for the other ligands were significantly smaller, and altogether the RMSE was reduced by 0.4 kcal mol−1. We link properties of the host-guest systems during simulation to errors in the computed free energies. Overall, we show that charged host-guest systems studied here, initialized in unconfirmed docking poses, present a challenge to accurate alchemical simulation methods.
Thermodynamic integration; Molecular dynamics; Docking; Host-guest; Blind prediction
Transcription factor IIS (TFIIS) is a protein known for catalyzing the cleavage reaction of the 3′-end of backtracked RNA transcript, allowing RNA polymerase II (Pol II) to reactivate the transcription process from the arrested state. Recent structural studies have provided a molecular basis of protein-protein interaction between TFIIS and Pol II. However, the detailed dynamic conformational changes of TFIIS upon binding to Pol II and the related thermodynamic information are largely unknown. Here we use computational approaches to investigate the conformational space of TFIIS in the Pol II-bound and Pol II-free (unbound) states. Our results reveal two distinct conformations of TFIIS: the closed and the open forms. The closed form is dominant in the Pol II-free (unbound) state of TFIIS, whereas the open form is favorable in the Pol II-bound state. Furthermore, we discuss the free energy difference involved in the conformational changes between the two forms in the presence or absence of Pol II. Additionally, our analysis indicates that hydrophobic interactions and the protein-protein interactions between TFIIS and Pol II are crucial for inducing the conformational changes of TFIIS. Our results provide novel insights into the functional interplay between Pol II and TFIIS as well as mechanism of reactivation of Pol II transcription by TFIIS.
accelerated molecular dynamics (aMD) method has recently been shown
to enhance the sampling of biomolecules in molecular dynamics (MD)
simulations, often by several orders of magnitude. Here, we describe
an implementation of the aMD method for the OpenMM application layer
that takes full advantage of graphics processing units (GPUs) computing.
The aMD method is shown to work in combination with the AMOEBA polarizable
force field (AMOEBA-aMD), allowing the simulation of long time-scale
events with a polarizable force field. Benchmarks are provided to
show that the AMOEBA-aMD method is efficiently implemented and produces
accurate results in its standard parametrization. For the BPTI protein,
we demonstrate that the protein structure described with AMOEBA remains
stable even on the extended time scales accessed at high levels of
accelerations. For the DNA repair metalloenzyme endonuclease IV, we
show that the use of the AMOEBA force field is a significant improvement
over fixed charged models for describing the enzyme active-site. The
new AMOEBA-aMD method is publicly available (http://wiki.simtk.org/openmm/VirtualRepository) and promises to be interesting for studying complex systems that
can benefit from both the use of a polarizable force field and enhanced
G-protein coupled receptors (GPCRs) mediate cellular responses to various hormones and neurotransmitters and are important targets for treating a wide spectrum of diseases.
G-protein coupled receptors (GPCRs) mediate cellular responses to various hormones and neurotransmitters and are important targets for treating a wide spectrum of diseases. They are known to adopt multiple conformational states (e.g., inactive, intermediate and active) during their modulation of various cell signaling pathways. Here, the free energy landscape of GPCRs is explored using accelerated molecular dynamics (aMD) simulations as demonstrated on the M2 muscarinic receptor, a key GPCR that regulates human heart rate and contractile forces of cardiomyocytes. Free energy profiles of important structural motifs that undergo conformational transitions upon GPCR activation and allosteric signaling are analyzed in detail, including the Arg3.50–Glu6.30 ionic lock, the Trp6.48 toggle switch and the hydrogen interactions between Tyr5.58–Tyr7.53.
We here present an improved version of AutoGrow (version 3.0), an evolutionary algorithm that works in conjunction with existing open-source software to automatically optimize candidate ligands for predicted binding affinity and other druglike properties. Though no substitute for the medicinal chemist, AutoGrow 3.0, unlike its predecessors, attempts to introduce some chemical intuition into the automated optimization process. AutoGrow 3.0 uses the rules of click chemistry to guide optimization, greatly enhancing synthesizability. Additionally, the program discards any growing ligand whose physical and chemical properties are not druglike. By carefully crafting chemically feasible druglike molecules, we hope that AutoGrow 3.0 will help supplement the chemist's efforts.
To demonstrate the utility of the program, we used AutoGrow 3.0 to generate predicted inhibitors of three important drug targets: T. brucei RNA editing ligase 1, peroxisome proliferator-activated receptor γ, and dihydrofolate reductase. In all cases, AutoGrow generated druglike molecules with high predicted binding affinities.
AutoGrow 3.0 is available free of charge (autogrow.ucsd.edu) under the terms of the GNU General Public License and has been tested on Linux and Mac OS X.
drug design; click chemistry; autogrow; computational chemistry
The nonmevalonate pathway is responsible for isoprenoid production in microbes, including H. pylori, M. tuberculosis and P. falciparum, but is nonexistent in humans, thus providing a desirable route for antibacterial and antimalarial drug discovery. We coordinate a structural study of IspH, a [4Fe-4S] protein responsible for converting HMBPP to IPP and DMAPP in the ultimate step in the nonmevalonate pathway. By performing accelerated molecular dynamics simulations on both substrate-free and HMBPP-bound [Fe4S4]2+ IspH, we elucidate how substrate binding alters the dynamics of the protein. Using principal component analysis, we note that while substrate-free IspH samples various open and closed conformations, the closed conformation observed experimentally for HMBPP-bound IspH is inaccessible in the absence of HMBPP. In contrast, simulations with HMBPP bound are restricted from accessing the open states sampled by the substrate-free simulations. Further investigation of the substrate-free simulations reveals large fluctuations in the HMBPP binding pocket, as well as allosteric pocket openings – both of which are achieved through the hinge motions of the individual domains in IspH. Coupling these findings with solvent mapping and various structural analyses reveals alternative druggable sites that may be exploited in future drug design efforts.
Drug resistance has recently entered into media conversations through the lens of MRSA (methicillin-resistant Staphylococcus aureus) infections, but conventional therapies are also failing to address resistance in cases of malaria and other bacterial infections, such as tuberculosis. To address these problems, we must develop new antibacterial and antimalarial medications. Our research focuses on understanding the structure and dynamics of IspH, an enzyme whose function is necessary for the survival of most bacteria and malaria-causing protozoans. Using computer simulations, we track how the structure of IspH changes in the presence and absence of its natural substrate. By inspecting the pockets that form in the normal motions of IspH, we propose a couple new routes by which new molecules may be developed to disrupt the function of IspH. It is our hope that these structural studies may be precursors to the development of novel therapies that may add to our current arsenal against bacterial and malarial infections.
Multi-scale modeling plays an important role in understanding the structure and biological functionalities of large biomolecular complexes. In this paper, we present an efficient computational framework to construct multi-scale models from atomic resolution data in the Protein Data Bank (PDB), which is accelerated by multi-core CPU and programmable Graphics Processing Units (GPU). A multi-level summation of Gaus-sian kernel functions is employed to generate implicit models for biomolecules. The coefficients in the summation are designed as functions of the structure indices, which specify the structures at a certain level and enable a local resolution control on the biomolecular surface. A method called neighboring search is adopted to locate the grid points close to the expected biomolecular surface, and reduce the number of grids to be analyzed. For a specific grid point, a KD-tree or bounding volume hierarchy is applied to search for the atoms contributing to its density computation, and faraway atoms are ignored due to the decay of Gaussian kernel functions. In addition to density map construction, three modes are also employed and compared during mesh generation and quality improvement to generate high quality tetrahedral meshes: CPU sequential, multi-core CPU parallel and GPU parallel. We have applied our algorithm to several large proteins and obtained good results.
efficient computation; multi-scale modeling; biomolecular complex * mesh generation; multi-core CPU; GPU
The relaxed complex scheme is an in silico drug
screening method that accounts for receptor flexibility by using molecular
dynamics simulations. Here, we used this approach combined with similarity
searches and experimental inhibition assays to identify several low micro-molar,
non-bisphosphonate inhibitors, bisamidines, of farnesyl diphosphate synthase
(FPPS), an enzyme targeted by some anti-cancer and anti-microbial agents and for
the treatment of bone resorption diseases. This novel class of FPPS inhibitors
have more drug-like properties than existing bisphosphonate inhibitors, making
them interesting pharmaceutical leads.
Molecular dynamics simulation using
enhanced sampling methods is
one of the powerful computational tools used to explore protein conformations
and free energy landscapes. Enhanced sampling methods often employ
either an increase in temperature or a flattening of the potential
energy surface to rapidly sample phase space, and a corresponding
reweighting algorithm is used to recover the Boltzmann statistics.
However, potential energies of complex biomolecules usually involve
large fluctuations on a magnitude of hundreds of kcal/mol despite
minimal structural changes during simulation. This leads to noisy
reweighting statistics and complicates the obtainment of accurate
final results. To overcome this common issue in enhanced conformational
sampling, we propose a scaled molecular dynamics method, which modifies
the biomolecular potential energy surface and employs a reweighting
scheme based on configurational populations. Statistical mechanical
theory is applied to derive the reweighting formula, and the canonical
ensemble of simulated structures is recovered accordingly. Test simulations
on alanine dipeptide and the fast folding polypeptide Chignolin exhibit
sufficiently enhanced conformational sampling and accurate recovery
of free energy surfaces and thermodynamic properties. The results
are comparable to long conventional molecular dynamics simulations
and exhibit better recovery of canonical statistics over methods which
employ a potential energy term in reweighting.
Thrombin is the central protease
in the cascade of blood coagulation
proteases. The structure of thrombin consists of a double β-barrel
core surrounded by connecting loops and helices. Compared to chymotrypsin,
thrombin has more extended loops that are thought to have arisen from
insertions in the serine protease that evolved to impart greater specificity.
Previous experiments showed thermodynamic coupling between ligand
binding at the active site and distal exosites. We present a combined
approach of molecular dynamics (MD), accelerated molecular dynamics
(AMD), and analysis of the residual local frustration of apo-thrombin
and active-site-bound (PPACK-thrombin). Community analysis of the
MD ensembles identified changes upon active site occupation in groups
of residues linked through correlated motions and physical contacts.
AMD simulations, calibrated on measured residual dipolar couplings,
reveal that upon active site ligation, correlated loop motions are
quenched, but new ones connecting the active site with distal sites
where allosteric regulators bind emerge. Residual local frustration
analysis reveals a striking correlation between frustrated contacts
and regions undergoing slow time scale dynamics. The results elucidate
a motional network that probably evolved through retention of frustrated
contacts to provide facile conversion between ensembles of states.
The synthetic host
cucurbituril (CB) binds aromatic guests
or metal complexes with ultrahigh affinity compared with that typically
displayed in protein–ligand binding. Due to its small size,
CB serves as an ideal receptor–ligand system for developing
computational methods for molecular recognition. Here, we apply the
recently developed variational implicit-solvent model (VISM), numerically
evaluated by the level-set method, to study hydration effects in the
high-affinity binding of the B2 bicyclo[2.2.2]octane derivative to
CB. For the unbound host, we find that the host cavity favors the
hydrated state over the dry state due to electrostatic effects. For
the guest binding, we find reasonable agreement to experimental binding
affinities. Dissection of the individual VISM free-energy contributions
shows that the major driving forces are water-mediated hydrophobic
interactions and the intrinsic (vacuum) host–guest van der
Waals interactions. These findings are in line with recent experiments
and molecular dynamics simulations with explicit solvent. It is expected
that the level-set VISM, with further refinement on the electrostatic
descriptions, can efficiently predict molecular binding and recognition
in a wide range of future applications.
The biased agonism of the G protein-coupled
where in addition to a traditional G protein-signaling pathway a GPCR
promotes intracellular signals though β-arrestin, is a novel
paradigm in pharmacology. Biochemical and biophysical studies have
suggested that a GPCR forms a distinct ensemble of conformations signaling
through the G protein and β-arrestin. Here we report on the
dynamics of the β2 adrenergic receptor bound to the
β-arrestin and G protein-biased agonists and the empty receptor
to further characterize the receptor conformational changes caused
by biased agonists. We use conventional and accelerated molecular
dynamics (aMD) simulations to explore the conformational transitions
of the GPCR from the active state to the inactive state. We found
that aMD simulations enable monitoring of the transition within the
nanosecond time scale while capturing the known microscopic characteristics
of the inactive states, such as the ionic lock, the inward position
of F6.44, and water clusters. Distinct conformational states are shown
to be stabilized by each biased agonist. In particular, in simulations
of the receptor with the β-arrestin-biased agonist N-cyclopentylbutanepherine, we observe a different pattern of motions
in helix 7 when compared to simulations with the G protein-biased
agonist salbutamol that involves perturbations of the network of interactions
within the NPxxY motif. Understanding the network of interactions
induced by biased ligands and the subsequent receptor conformational
shifts will lead to development of more efficient drugs.
is one of the prime tools for high resolution protein structure
refinement. While its scoring function can distinguish native-like
from non-native-like conformations in many cases, the method is limited
by conformational sampling for larger proteins, that is, leaving a
local energy minimum in which the search algorithm may get stuck.
Here, we test the hypothesis that iteration of Rosetta with an orthogonal
sampling and scoring strategy might facilitate exploration of conformational
space. Specifically, we run short molecular dynamics (MD) simulations
on models created by de novo folding of large proteins
into cryoEM density maps to enable sampling of conformational space
not directly accessible to Rosetta and thus provide an escape route
from the conformational traps. We present a combined MD–Rosetta
protein structure refinement protocol that can overcome some
of these sampling limitations. Two of four benchmark proteins showed
incremental improvement through all three rounds of the iterative
refinement protocol. Molecular dynamics is most efficient in applying
subtle but important rearrangements within secondary structure elements
and is thus highly complementary to the Rosetta refinement, which
focuses on side chains and loop regions.
compare established docking programs, AutoDock Vina and Schrödinger’s
Glide, to the recently published NNScore scoring functions. As expected,
the best protocol to use in a virtual-screening project is highly
dependent on the target receptor being studied. However, the mean
screening performance obtained when candidate ligands are docked with
Vina and rescored with NNScore 1.0 is not statistically different
than the mean performance obtained when docking and scoring with Glide.
We further demonstrate that the Vina and NNScore docking scores both
correlate with chemical properties like small-molecule size and polarizability.
Compensating for these potential biases leads to improvements in virtual
screen performance. Composite NNScore-based scoring functions suited
to a specific receptor further improve performance. We are hopeful
that the current study will prove useful for those interested in computer-aided
The Adaptive Poisson-Boltzmann Solver (APBS) is a state-of-the-art suite for performing Poisson-Boltzmann electrostatic calculations on biomolecules. The iAPBS package provides a modular programmatic interface to the APBS library of electrostatic calculation routines. The iAPBS interface library can be linked with a FORTRAN or C/C++ program thus making all of the APBS functionality available from within the application. Several application modules for popular molecular dynamics simulation packages – Amber, NAMD and CHARMM are distributed with iAPBS allowing users of these packages to perform implicit solvent electrostatic calculations with APBS.
Group VI Ca2+-independent phospholipase A2 (iPLA2) is a water-soluble enzyme that is active when associated with phospholipid membranes. Despite its clear pharmaceutical relevance, no X-ray or NMR structural information is currently available for the iPLA2 or its membrane complex. In this paper, we combine homology modeling with coarse-grained (CG) and all-atom (AA) molecular dynamics (MD) simulations to build structural models of iPLA2 in association with a phospholipid bilayer. CG-MD simulations of the membrane insertion process were employed to provide a starting point for an atomistic description. Six AA-MD simulations were then conducted for 60 ns, starting from different initial CG structures, to refine the membrane complex. The resulting structures are shown to be consistent with each other and with deuterium exchange mass spectrometry (DXMS) experiments, suggesting that our approach is suitable for the modeling of iPLA2 at the membrane surface. The models show that an anchoring region (residues 710–724) forms an amphipathic helix that is stabilized by the membrane. In future studies, the proposed iPLA2 models should provide a structural basis for understanding the mechanisms of lipid extraction and drug-inhibition. In addition, the dual-resolution approach discussed here should provide the means for the future exploration of the impact of lipid diversity and sequence mutations on the activity of iPLA2 and related enzymes.
The Ca2+-independent phospholipase A2 (iPLA2) enzyme is a potential target for the development of medicinal agents against heart and neurological diseases, multiple sclerosis, arthritis, and cancer. However, no structural information is currently available for the iPLA2. The binding of the enzyme to human membranes is driven by favorable electrostatic and non-polar interactions, but the detailed influence of these factors is not well understood. In this paper, we have combined coarse-grained and all-atom simulations of a homology model of the iPLA2. The coarse-grained description allows highly efficient simulations of the protein insertion into a lipid bilayer, while the all-atom simulations are used to refine the structures of the protein–membrane complexes. Finally, the resulting structures are validated experimentally with deuterium exchange experiments. In future works, this approach could be used to build models of other PLA2s. The iPLA2 models presented here open the door to the computational design of new inhibitors with improved potency and selectivity.
Protein flexibility plays a major role in biomolecular recognition. In many cases it is not obvious how molecular structure will change upon association with other molecules. In proteins these changes can be major, with large deviations in overall backbone structure, or they can be more subtle as in a side chain rotation. Either way the algorithms that predict the favorability of biomolecular association require relatively accurate predictions of the bound structure to give an accurate assessment of the energy involved in association. Here we review a number of techniques that have been proposed to accommodate receptor flexibility in the simulation of small molecules binding to protein receptors. We investigate modifications to standard rigid receptor docking algorithms, and also explore enhanced sampling techniques, and the combination of free energy calculations and enhanced sampling techniques. The understanding and allowance for receptor flexibility are helping to make computer simulations of ligand protein binding more accurate. These developments may help improve the efficiency of drug discovery and development. Efficiency will be essential as we begin to see personalized medicine tailored to individual patients, which means specific drugs are needed for each patient’s genetic makeup.
Computer aided drug design; structure based drug design; receptor flexibility; ensemble docking; relaxed complex scheme; molecular dynamics; accelerated molecular dynamics; free energy calculation
During the past century, several epidemics of human African trypanosomiasis, a deadly disease caused by the protist Trypanosoma brucei, have afflicted sub-Saharan Africa. Over 10,000 new victims are reported each year, with hundreds of thousands more at risk. As current drug treatments are either highly toxic or ineffective, novel trypanocides are urgently needed. The T. brucei galactose-synthesis pathway is one potential therapeutic target. Though galactose is essential for T. brucei survival, the parasite lacks the transporters required to intake galactose from the environment. UDP-galactose 4′-epimerase (TbGalE) is responsible for the epimerization of UDP-glucose to UDP-galactose and so is of great interest to medicinal chemists. Using molecular dynamics simulations, we investigate the atomistic motions of TbGalE in both the apo and holo states. The sampled conformations and protein dynamics depend not only on the presence of a UDP-sugar ligand, but also on the chirality of the UDP-sugar C4 atom. This dependence provides important insights into TbGalE function and may help guide future computer-aided drug-discovery efforts targeting this protein.
TbGalE; Trypanosoma brucei; UDP-Galactose-4’-Epimerase; African Sleeping Sickness; Molecular Dynamics; Protein Structure
In this paper we propose a nonlinear elasticity model of macromolecular conformational change (deformation) induced by electrostatic forces generated by an implicit solvation model. The Poisson-Boltzmann equation for the electrostatic potential is analyzed in a domain varying with the elastic deformation of molecules, and a new continuous model of the electrostatic forces is developed to ensure solvability of the nonlinear elasticity equations. We derive the estimates of electrostatic forces corresponding to four types of perturbations to an electrostatic potential field, and establish the existance of an equilibrium configuration using a fixed-point argument, under the assumption that the change in the ionic strength and charges due to the additional molecules causing the deformation are sufficiently small. The results are valid for elastic models with arbitrarily complex dielectric interfaces and cavities, and can be generalized to large elastic deformation caused by high ionic strength, large charges, and strong external fields by using continuation methods.
Macromolecular Conformational Change; Nonlinear Elasticity; Continuum Modeling; Poisson-Boltzmann equation; Electrostatic Force; Coupled System; Fixed Point
The protozoan parasite Trypanosoma cruzi, the etiological agent of Chagas’ disease, affects millions of individuals and continues to be an important global health concern. The poor efficacy and unfavorable side effects of current treatments necessitate novel therapeutics. Cruzain, the major cysteine protease of T. cruzi, is one potential novel target. Recent advances in a class of vinyl-sulfone inhibitors are encouraging; however, as most potential therapeutics fail in clinical trials and both disease progression and resistance call for combination therapy with several drugs, the identification of additional classes of inhibitory molecules is essential. Using an exhaustive virtual-screening and experimental-validation approach, we identify several additional small-molecule cruzain inhibitors. Further optimization of these chemical scaffolds could lead to the development of novel drugs useful in the treatment of Chagas’ disease.
cruzain; cruzipain; Chagas’ disease; Trypanosoma cruzi; computer-aided drug discovery; cysteine protease inhibitor