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Maxim Totrov

Publications and source records attributed to Maxim Totrov.

17 recordsLinked to original sources
PubMed2006

Waltzing transporters and 'the dance macabre' between humans and bacteria.

Multidrug-resistance efflux pumps - in particular those belonging to the resistance-nodulation-cell-division (RND) family of transporters, with their unusually high degree of substrate promiscuity - significantly restrict the effectiveness of antibacterial therapy. Recent years have heralded remarkable insights into the structure and mechanisms of these fascinating molecular machines. Here, we review recent advances in the field and describe various approaches used in combating efflux-mediated resistance.

ATP Binding Cassette Transporter, Subfamily B↗
PubMed2005

Improving CAPRI predictions: optimized desolvation for rigid-body docking.

The ICM Docking and Interface Side-Chain Optimization (ICM-DISCO) showed promising predictive results during the first CAPRI experiment by successfully finding medium- or high-accuracy models in 3 of the 7 targets. A key factor was the ability to recognize near-native rigid-body geometries in a relatively low number of alternative docking poses, together with the successful refinement of the rigid-body docking interfaces. Since then, we have focused on improving the scoring function to optimally discriminate the near-native rigid-body conformations. For that, we have defined a new desolvation descriptor for rigid-body docking, based on atomic solvation parameters (ASPs) derived from octanol-water transfer experiments. This and other new approaches have been gradually incorporated into our docking procedure during our participation on the second CAPRI experiment. Overall, we produced reasonable models for 8 of the 9 official targets. Especially encouraging were those cases in which a homology model of 1 of the subunits had to be used during the docking simulations. And not less gratifying has been the successful prediction of antibody-antigen targets in a completely automatic, unrestrained fashion. In summary, our success rate (89%) shows a consistent improvement over the previous CAPRI rounds, and suggests that a correct desolvation description is key for improved protein-protein docking predictions.

Algorithms↗
PubMed2005

Pocketome via comprehensive identification and classification of ligand binding envelopes.

We developed a new computational algorithm for the accurate identification of ligand binding envelopes rather than surface binding sites. We performed a large scale classification of the identified envelopes according to their shape and physicochemical properties. The predicting algorithm, called PocketFinder, uses a transformation of the Lennard-Jones potential calculated from a three-dimensional protein structure and does not require any knowledge about a potential ligand molecule. We validated this algorithm using two systematically collected data sets of ligand binding pockets from complexed (bound) and uncomplexed (apo) structures from the Protein Data Bank, 5616 and 11,510, respectively. As many as 96.8% of experimental binding sites were predicted at better than 50% overlap level. Furthermore 95.0% of the asserted sites from the apo receptors were predicted at the same level. We demonstrate that conformational differences between the apo and bound pockets do not dramatically affect the prediction results. The algorithm can be used to predict ligand binding pockets of uncharacterized protein structures, suggest new allosteric pockets, evaluate feasibility of protein-protein interaction inhibition, and prioritize molecular targets. Finally the data base of the known and predicted binding pockets for the human proteome structures, the human pocketome, was collected and classified. The pocketome can be used for rapid evaluation of possible binding partners of a given chemical compound.

Algorithms↗
PubMed2004

A novel class of inhibitors of peptide deformylase discovered through high-throughput screening and virtual ligand screening.

Peptide deformylase (PDF) has been identified as a promising antibacterial and herbicide target. A structurally novel class of inhibitors containing a 2-thioxo-thiazolidin-4-one heterocycle substituted by an arylidene group at the 5-position and a hexanoic acid side chain at the 3-position was discovered independently via high-throughput screening and virtual ligand screening. Data mining and analogue synthesis established a structure--activity relationship for the side chain region that is consistent with the docked structure.

Amidohydrolases↗
PubMed2004

Identification of protein-protein interaction sites from docking energy landscapes.

Protein recognition is one of the most challenging and intriguing problems in structural biology. Despite all the available structural, sequence and biophysical information about protein-protein complexes, the physico-chemical patterns, if any, that make a protein surface likely to be involved in protein-protein interactions, remain elusive. Here, we apply protein docking simulations and analysis of the interaction energy landscapes to identify protein-protein interaction sites. The new protocol for global docking based on multi-start global energy optimization of an all-atom model of the ligand, with detailed receptor potentials and atomic solvation parameters optimized in a training set of 24 complexes, explores the conformational space around the whole receptor without restrictions. The ensembles of the rigid-body docking solutions generated by the simulations were subsequently used to project the docking energy landscapes onto the protein surfaces. We found that highly populated low-energy regions consistently corresponded to actual binding sites. The procedure was validated on a test set of 21 known protein-protein complexes not used in the training set. As much as 81% of the predicted high-propensity patch residues were located correctly in the native interfaces. This approach can guide the design of mutations on the surfaces of proteins, provide geometrical details of a possible interaction, and help to annotate protein surfaces in structural proteomics.

Binding Sites↗
PubMed2004

Accurate and efficient generalized born model based on solvent accessibility: derivation and application for LogP octanol/water prediction and flexible peptide docking.

A novel method for fast and accurate evaluation of the generalized Born radii in macromolecular solvation electrostatics calculations is proposed, based on the solvent accessibility of the first two solvation layers around an atom. The reverse generalized Born radii calculated by the method have correlation coefficient of 98.7% and RMSD of 0.031 A(-1) with the values obtained using a precise but significantly slower numerical boundary element solution. The method is applied to derive an estimate of the free solvation energy difference between octanol and water and to predict LogP octanol-water. A nine-parameter model is optimized on an 81 compound training set and applied to predict LogP(ow) for an external evaluation set of 19 drug molecules with RMSD of 0.9. The new GB approximation is also tested in Monte Carlo docking simulations of the fully flexible p53 peptide fragment to MDM2. The best energy solution found in the simulations has RMSD of 2.8 A to the X-ray structure.

Algorithms↗
PubMed2004

Comprehensive identification of "druggable" protein ligand binding sites.

We have developed a new computational algorithm for de novo identification of protein-ligand binding pockets and performed a large-scale validation of the algorithm on two systematically collected datasets from all crystallographic structures in the Protein Data Bank (PDB). This algorithm, called DrugSite, takes a three-dimensional protein structure as input and returns the location, volume and shape of the putative small molecule binding sites by using a physical potential and without any knowledge about a potential ligand molecule. We validated this method using 17,126 binding sites from complexes and apo-structures from the PDB. Out of 5,616 binding sites from protein-ligand complexes, 98.8% were identified by predicted pockets. In proteins having known binding sites, 80.9% were predicted by the largest predicted pocket and 92.7% by the first two. The average ratio of predicted contact area to the total surface area of the protein was 4.7% for the predicted pockets. In only 1.2% of the cases, no "pocket density" was found at the ligand location. Further, 98.6% of 11,510 binding sites collected from apo-structures were predicted. The algorithm is accurate and fast enough to predict protein-ligand binding sites of uncharacterized protein structures, suggest new allosteric druggable pockets, evaluate druggability of protein-protein interfaces and prioritize molecular targets by druggability. Furthermore, the known and the predicted binding pockets for the proteome of a particular organism can be clustered into a "pocketome", that can be used for rapid evaluation of possible binding partners of a given chemical compound.

Algorithms↗
PubMed2003

Nuclear hormone receptor targeted virtual screening.

Virtual library screening (VLS) is emerging as a valuable drug lead discovery tool. ICM-VLS implementation of this technology was evaluated on a benchmark set of nuclear hormone receptors (NRs), an important therapeutic target family. Over 5000 structurally diverse compounds, including 78 known NR ligands, were screened against 18 crystal structures and one computer model of 10 NR ligand binding domains in their active or inactive states. The results confirm the ability of the VLS method to generate highly focused subsets of the input chemical library, enriched 33- to 100-fold for all but one receptor studied. However, receptor flexibility remains to be fully addressed, and the choice of the specific conformation used for screening may determine the success of the exercise. We observe that for a particular ligand VLS can often identify the correct target within the receptor family, although the technology is unable to reliably discriminate between the closely related receptor isoforms. Additionally, our results suggest that VLS may be applied successfully without an experimental structure of the receptor by using a homology model. These data represent a realistic snapshot of the state-of-the-art of NR-targeted VLS and define the recent progress and the remaining limitations of the technology.

Crystallography, X-Ray↗
PubMed2003

ICM-DISCO docking by global energy optimization with fully flexible side-chains.

The ICM-DISCO (Docking and Interface Side-Chain Optimization) protein-protein-docking method is a direct stochastic global energy optimization from multiple starting positions of the ligand. The first step is performed by docking of a rigid all-atom ligand molecule to a set of soft receptor potentials precalculated on a 0.5 A grid from realistic solvent-corrected force-field energies. This step finds the correct solution as the lowest energy conformation in almost 100% of the cases in which interfaces do not change on binding. The second step is needed to deal with the induced changes and includes the global optimization of the interface side-chains of up to 400 best solutions. The CAPRI predictions were performed fully automatically with this method. Available experimental information was included as a filtering step to favor expected docking surfaces. In three of the seven proposed targets, the ICM-DISCO method found a good solution (>50% of correct contacts) within the five submitted models. The procedure is global and fully automated. We demonstrate that the algorithm handles the induced changes of surface side-chains but is less successful if the backbone undergoes large-scale rearrangements.

Algorithms↗
PubMed2003

Discovery of diverse thyroid hormone receptor antagonists by high-throughput docking.

Treatment of hyperthyroidism, a common clinical condition that can have serious manifestations in the elderly, has remained essentially unchanged for >30 years. Directly antagonizing the effect of the thyroid hormone at the receptor level may be a significant improvement for the treatment of hyperthyroid patients. We built a computer model of the thyroid hormone receptor (TR) ligand-binding domain in its predicted antagonist-bound conformation and used a virtual screening algorithm to select 100 TR antagonist candidates out of a library of >250,000 compounds. We were able to obtain 75 of the compounds selected in silico and studied their ability to act as antagonists by using cultured cells that express TR. Fourteen of these compounds were found to antagonize the effect of T3 on TR with IC50s ranging from 1.5 to 30 microM. A small virtual library of compounds, derived from the highest affinity antagonist (1-850) that could be rapidly synthesized, was generated. A second round of virtual screening identified new compounds with predicted increased antagonist activity. These second generation compounds were synthesized, and their ability to act as TR antagonists was confirmed by transfection and receptor binding experiments. The extreme structural diversity of the antagonist compounds shows how receptor-based virtual screening can identify diverse chemistries that comply with the structural rules of TR antagonism.

Drug Design↗
PubMed2003

ICFF: a new method to incorporate implicit flexibility into an internal coordinate force field.

We introduce a new method to accurately "project" a Cartesian force field onto an internal coordinate molecular model with fixed-bond geometry. The algorithm automatically generates the Internal Coordinate Force Field (ICFF), which is a close approximation of the "source" Cartesian force field. The ICFF method reduces the number of free variables in a model by at least 10-fold and facilitates the fast convergence of geometry optimizations, an advantage that is critical for many applications such as the docking of flexible ligands or conformational modeling of macromolecules. Although covalent geometry is fixed in an ICFF model, implicit flexibility is incorporated into the force field parameters in the following two ways. First, we formulate an empirical torsion energy term in ICFF as a sixfold Fourier series and develop a procedure to calculate the Fourier coefficients from the conformational energy profiles of the fully flexible Cartesian model. The ICFF torsion parameters thus represent not only torsion component of the source force field, but also bond bending, bond stretching, and "1-4" van der Waals interactions. Second, we use a soft polynomial repulsion function for "1-5" and "1-6" interactions to mimic the flexibility of bonds, connecting these atoms. Also, we suggest a way to use a local part of the Cartesian force field to automatically generate fixed covalent geometries, compatible with the ICFF energy function. Here, we present an implementation of the ICFF algorithm, which employs the MMFF94s Cartesian force field as a "source." Extensive benchmarking of ICFF with a representative set of organic molecules demonstrates that the implicit flexibility model accurately reproduces MMFF94s equilibrium conformational energy differences (RMSD approximately 0.64 kcal) and, most importantly, detailed torsion energy profiles (RMSD approximately 0.37 kcal). This accuracy is characteristic of the method, because all the ICFF parameters (except one scaling factor in the "1-5,1-6" repulsion term) are derived directly from the source Cartesian force field and do not depend on any particular molecular set. In contrast, the rigid geometry model with the MMFF94s energy function yields highly biased estimations in this test with the RMSD exceeding 1.2 kcal for the equilibrium energy comparisons and approximately 3.4 kcal for the torsion energy profiles.

Journal Article↗
PubMed2003

Comparative study of several algorithms for flexible ligand docking.

We have performed a comparative assessment of several programs for flexible molecular docking: DOCK 4.0, FlexX 1.8, AutoDock 3.0, GOLD 1.2 and ICM 2.8. This was accomplished using two different studies: docking experiments on a data set of 37 protein-ligand complexes and screening a library containing 10,037 entries against 11 different proteins. The docking accuracy of the methods was judged based on the corresponding rank-one solutions. We have found that the fraction of molecules docked with acceptable accuracy is 0.47, 0.31, 0.35, 0.52 and 0.93 for, respectively, AutoDock, DOCK, FlexX, GOLD and ICM. Thus ICM provided the highest accuracy in ligand docking against these receptors. The results from the other programs are found to be less accurate and of approximately the same quality. A speed comparison demonstrated that FlexX was the fastest and AutoDock was the slowest among the tested docking programs. The database screening was performed using DOCK, FlexX and ICM. ICM was able to identify the original ligands within the top 1% of the total library in 17 cases. The corresponding number for DOCK and FlexX was 7 and 8, respectively. We have estimated that in virtual database screening, 50% of the potentially active compounds will be found among approximately 1.5% of the top scoring solutions found with ICM and among approximately 9% of the top scoring solutions produced by DOCK and FlexX.

Algorithms↗
PubMed2002

Structural model of nicotinic acetylcholine receptor isotypes bound to acetylcholine and nicotine.

BACKGROUND: Nicotine is a psychoactive drug presenting a diverse array of biological activities, some positive, such as enhancement of cognitive performances, others negative, such as addiction liability. Ligands that discriminate between the different isotypes of nicotinic acetylcholine receptors (nAChRs) could present improved pharmacology and toxicity profile. RESULTS: Based on the recent crystal structure of a soluble acetylcholine binding protein from snails, we have built atomic models of acetylcholine and nicotine bound to the pocket of four different human nAChR subtypes. The structures of the docked ligands correlate with available biochemical data, and reveal that the determinants for isotype selectivity are relying essentially on four residues, providing diversity of the ligand binding pocket both in terms of Van der Waals boundary, and electrostatic potential. We used our models to screen in silico a large compound database and identify a new ligand candidate that could display subtype selectivity. CONCLUSION: The nAChR-agonist models should be useful for the design of nAChR agonists with diverse specificity profiles.

Acetylcholine↗
PubMed2002

Soft protein-protein docking in internal coordinates.

The association of two biological macromolecules is a fundamental biological phenomenon and an unsolved theoretical problem. Docking methods for ab initio prediction of association of two independently determined protein structures usually fail when they are applied to a large set of complexes, mostly because of inaccuracies in the scoring function and/or difficulties on simulating the rearrangement of the interface residues on binding. In this work we present an efficient pseudo-Brownian rigid-body docking procedure followed by Biased Probability Monte Carlo Minimization of the ligand interacting side-chains. The use of a soft interaction energy function precalculated on a grid, instead of the explicit energy, drastically increased the speed of the procedure. The method was tested on a benchmark of 24 protein-protein complexes in which the three-dimensional structures of their subunits (bound and free) were available. The rank of the near-native conformation in a list of candidate docking solutions was <20 in 85% of complexes with no major backbone motion on binding. Among them, as many as 7 out of 11 (64%) protease-inhibitor complexes can be successfully predicted as the highest rank conformations. The presented method can be further refined to include the binding site predictions and applied to the structures generated by the structural proteomics projects. All scripts are available on the Web.

Algorithms↗
PubMed2002

Screened charge electrostatic model in protein-protein docking simulations.

A new method for considering solvation when calculating electrostatics for protein docking is proposed. The solvent-exposed charges are attenuated by induced solvent polarization charges. Modified charges are pre-calculated and the correction doesn't affect the speed of the actual simulation. The new Screened Charge Electrostatic Model (SChEM) results in an improved discrimination of near-native solutions from false positives in docking simulations as compared to conventional 'non-solvated' charge assignment. A series of protein-protein complexes were analyzed by running automated rigid-body Monte-Carlo docking simulations using the 3-D coordinates of the unbound components. In all but one case, the use of solvation screened charges for electrostatic calculations helped to improve the rank of the near-native solution after rigid-body simulations. The SChEM also drastically improved the results of the subsequent refinement of the interface side-chains. In all cases the final lowest energy solution was found within 3.0 A r.m.s.d. of the crystal structure.

Animals↗