Chapman University

Publications: 1995-1999


D. Bouzida, P. Rejto, S. Arthurs, A. B. Colson, S.T. Freer, D. K. Gehlhaar, V. Larson, B. A. Luty, P. W. Rose, G. M. Verkhivker. Computer simulations of ligand-protein binding with ensembles of protein conformations: a Monte Carlo study of HIV-1 protease binding energy landscapes. Int. J. Quantum Chemistry 72(1): 73-84,1999. Abstract.

ABSTRACT: We present the results of molecular docking simulations with HIV-1 protease for the sb203386 and skf107457 inhibitors by Monte Carlo simulated annealing. A simplified piecewise linear energy function, the standard AMBER force field, and the AMBER force field with solvation and a soft-core smoothing component are employed in simulations with a single-protein conformation to determine the relationship between docking simulations with a simple energy function and more realistic force fields. The temperature-dependent binding free energy profiles of the inhibitors interacting with a single protein conformation provide a detailed picture of relative thermodynamic stability and a distribution of ligand binding modes in agreement with experimental crystallographic data. Using the simplified piecewise linear energy function, we also performed Monte Carlo docking simulations with an ensemble of protein conformations employing preferential biased sampling of low-energy protein conformations, and the results are analyzed in connection with the free energy profiles.

P. Rejto, D. Bouzida, G. Verkhivker. Examining ligand--protein interactions in drug discovery with binding energy landscapes. Theor. Chem. Acc. 101:138-142, 1999. Abstract.

ABSTRACT: Binding-energy landscapes are used to investigate the thermodynamics of molecular recognition for the pteridine ring, a recognition anchor in binding with dihydrofolate reductase, and two molecules with the same shape but different heteroatom substitutions. The relative importance of hydrogen bonding and hydrophobic interactions in this system is analyzed by comparing these three different decorations of the pteridine scaffold.

D. Bouzida, P. Rejto, G. Verkhivker. A Monte-Carlo study of ligand-protein binding energy landscape with the weighted analysis histogram methods. Int. J. Quantum Chemistry 73 (2):113-121, 1999. Abstract.

ABSTRACT: The thermodynamics of molecular recognition is investigated by a statistical energy landscape approach, where the temperature profile of the ligand–protein binding process is determined using the weighted histogram analysis method. The analysis reveals differences in the binding energy landscapes of two molecular fragments with the FKBP12 protein, which are reflected in their characteristic transition temperatures. The approach provides insight into the nature of transitions between unbound and bound phases of ligand–protein complexes. One molecular fragment proceeds from the unbound phase to the native complex via a short-lived intermediate at relatively high temperature. The second fragment has a significantly more rugged binding energy landscape and goes from unbound to a long-lived nonspecific bound species consisting of isoenergetic yet structurally different binding modes, and later via a second-order-like transition to the native complex. Emerging universalities in molecular recognition and protein folding mechanisms are highlighted in the context of the kinetic partitioning mechanism.

G. M. Verkhivker, P.A. Rejto, D. Bouzida, S. Arthurs, A. B. Colson, S.T. Freer, D. K. Gehlhaar, V. Larson, B. A. Luty, T. Marrone and P. W. Rose. Towards understanding the mechanisms of molecular recognition by computer simulations of ligand--protein interactions. J. Mol. Recognit. 12(6): 371-389, 1999. PUBMED. Abstract.

ABSTRACT: The thermodynamic and kinetic aspects of molecular recognition for the methotrexate (MTX)–dihydrofolate reductase (DHFR) ligand–protein system are investigated by the binding energy landscape approach. The impact of ‘hot’ and ‘cold’ errors in ligand mutations on the thermodynamic stability of the native MTX–DHFR complex is analyzed, and relationships between the molecular recognition mechanism and the degree of ligand optimization are discussed. The nature and relative stability of intermediates and thermodynamic phases on the ligand–protein association pathway are studied, providing new insights into connections between protein folding and molecular recognition mechanisms, and cooperativity of ligand– protein binding. The results of kinetic docking simulations are rationalized based on the thermodynamic properties determined from equilibrium simulations and the shape of the underlying binding energy landscape. We show how evolutionary ligand selection for a receptor active site can produce well-optimized ligand–protein systems such as MTX–DHFR complex with the thermodynamically stable native structure and a direct transition mechanism of binding from unbound conformations to the unique native structure.

D. Bouzida, S. Arthurs, A. B. Colson, S.T. Freer, D. K. Gehlhaar, V. Larson, B. A. Luty, P.A. Rejto, P. W. Rose, G. M. Verkhivker. Thermodynamics and kinetics of ligand--protein binding studied with the weighted histogram analysis method and simulated annealing. In “Pacific Symposium on Biocomputing-99”. World Scientific, Singapore, p.426-437, 1999. PUBMED. Abstract.

ABSTRACT: The thermodynamics of ligand{protein molecular recognition is investigated by the energy landscape approach for two systems: methotrexate(MTX){dihydrofolate reductase(DHFR) and biotin{streptavidin. The temperature{dependent binding free energy pro le is determined using the weighted histogram analysis method. Two di erent force elds are employed in this study: a simpli ed model of ligand{ protein interactions and the AMBER force eld with a soft core smoothing component, used to soften the repulsive part of the potential. The results of multiple docking simulations are rationalized from the shape of the binding free energy pro le that characterizes the thermodynamics of the binding process.


L. Schaffer, G. Verkhivker. Predicting structural effects in HIV-1 protease mutant complexes with flexible ligand docking and protein side-chain optimization. Proteins: Struct. Funct. Genet. 33(2):1-16, 1998. PUBMED. Abstract.

ABSTRACT: We present a computational approach for predicting structures of ligand-protein complexes and analyzing binding energy landscapes that combines Monte Carlo simulated annealing technique to determine the ligand bound conformation with the dead-end elimination algorithm for side-chain optimization of the protein active site residues. Flexible ligand docking and optimization of mobile protein side-chains have been performed to predict structural effects in the V32I/I47V/V82I HIV-1 protease mutant bound with the SB203386 ligand and in the V82A HIV-1 protease mutant bound with the A77003 ligand. The computational structure predictions are consistent with the crystal structures of these ligand-protein complexes. The emerging relationships between ligand docking and side-chain optimization of the active site residues are rationalized based on the analysis of the ligand-protein binding energy landscape.

P. Rejto, G. Verkhivker. Molecular anchors with large stability gaps ensure linear free energy relationships in ligand--protein binding. In “Pacific Symposium on Biocomputing-98”. World Scientific, Singapore, p. 362-373, 1998. PUBMED. Abstract.

ABSTRACT: Ligand{protein docking simulations are employed to analyze the binding energy landscape of the pipecolinyl fragment that serves as a recognition core of the FK506 ligand in binding with the FKBP12 protein. This fragment acts as a molecular an- chor that speci cally binds within the protein active site in a unique binding mode, in harmony with the structure of the FK506{FKBP12 complex. Molecular anchors are characterized by a large stability gap, de ned to be the free energy of a ligand bound in the native binding mode relative to the free energy of alternative binding modes. For ligands that share a common anchor fragment, a linear binding free energy relationship may be expected for hydrophobic substituents provided they do not abrogate the anchor binding mode. Changes in solvent{accessible surface area for these peripheral groups are used to rationalize the relative binding anities of a series of FKBP12{ligand complexes which share the pipecolinyl anchor fragment. A series of benzene derivatives that bind to a mutant form of T4 lysozyme is also analyzed, and implications for structure{based drug design are discussed.


P. Rejto, G. Verkhivker. Mean field analysis of FKBP12 complexes with FK506 and rapamycin: implications for a role of crystallographic water molecules in molecular recognition and specificity. Proteins: Struct. Funct. Genet. 28:313-324, 1997. PUBMED. Abstract.

ABSTRACT: Mean field analysis of FKBP12 complexes with FK506 and rapamycin has been performed by using structures obtained from molecular docking simulations on a simple, yet robust molecular recognition energy landscape. When crystallographic water molecules are included in the simulations as an extension of the FKBP12 protein surface, there is an appreciable stability gap between the energy of the native FKBP12–FK506 complex and energies of conformations with the “native-like” binding mode. By contrast, the energy spectrum of the FKBP12–rapamycin complex is dense regardless of the presence of the water molecules. The stability gap in the FKBP12–FK506 system is determined by two critical water molecules from the effector region that participate in a network of specific hydrogen bond interactions. This interaction pattern protects the integrity and precision of the composite ligand-protein effector surface in the binary FKBP12–FK506 complex and is preserved in the crystal structure of the FKBP12–FK506–calcineurin ternary complex. These features of the binding energy landscapes provide useful insights into specific and nonspecific aspects of FK506 and rapamycin recognition.

N. Shah, P. Rejto, G. Verkhivker. Structural consensus in ligand-protein docking identifies recognition peptide motifs that bind streptavidin. Proteins: Struct. Funct. Genet. 28:421-433, 1997. PUBMED. Abstract.

ABSTRACT: Computational structure prediction of streptavidin-peptide complexes for known recognition sequences and a number of random di-, tri-, and tetrapeptides has been conducted, and mechanisms of peptide recognition with streptavidin have been investigated by a new computational protocol. The structural consensus criterion, which is computed from multiple docking simulations and measures the accessibility of the dominant binding mode, identifies recognition motifs from a set of random peptide sequences, whereas energetic analysis is less discriminatory. The predicted conformations of recognition tripeptide and tetrapeptide sequences are also in structural harmony and composed of peptide fragments that are individually unfrustrated in their bound conformation, resulting in a minimally frustrated energy landscape for recognition peptides.


G. Verkhivker, P. Rejto. A mean field model of ligand-protein interactions : Implications for the structural assessment of HIV-1 protease complexes and receptor-specific binding. Proc. Nat.. Acad. Sci. U.S.A. 93: 60-64, 1996. PUBMED. Abstract.

ABSTRACT: We propose a general mean field model of ligand-protein interactions to determine the thermodynamic equilibrium of a system at finite temperature. The method is employed in structural assessments of two human immunodeficiency virus type 1 protease complexes where the gross effects of protein flexibility are incorporated by utilizing a data base of crystal structures. Analysis of the energy spectra for these complexes has revealed that structural and thermodynamic aspects of molecular recognition can be rationalized on the basis of the extent of frustration in the binding energy landscape. In particular, the relationship between receptorspecific binding of these ligands to human immunodeficiency virus type 1 protease and a minimal frustration principle is analyzed.

P. Rejto, G. Verkhivker. Unraveling principles of lead discovery : from unfrustrated energy landscapes to novel molecular anchors. Proc. Nat. Acad. Sci. U.S.A. 93 : 8945-8950, 1996. PUBMED. Abstract.

ABSTRACT: The search for novel leads is a critical step in the drug discovery process. Computational approaches to identify new lead molecules have focused on discovering complete ligands by evaluating the binding affinity of a large number of candidates, a task of considerable complexity. A new computational method is introduced in this work based on the premise that the primary molecular recognition event in the protein binding site may be accomplished by small core fragments that serve as molecular anchors, providing a structurally stable platform that can be subsequently tailored into complete ligands. To fulfill its role, we show that an effective molecular anchor must meet both the thermodynamic requirement of relative energetic stability of a single binding mode and its consistent kinetic accessibility, which may be measured by the structural consensus of multiple docking simulations. From a large number of candidates, this technique is able to identify known core fragments responsible for primary recognition by the FK506 binding protein (FKBP-12), along with a diverse repertoire of novel molecular cores. By contrast, absolute energetic criteria for selecting molecular anchors are found to be promiscuous. A relationship between a minimum frustration principle of binding energy landscapes and receptor-specific molecular anchors in their role as "recognition nuclei" is established, thereby unraveling a mechanism of lead discovery and providing a practical route to receptor-biased computational combinatorial chemistry.

G. Verkhivker, P. Rejto, D.K. Gehlhaar, S.T. Freer. Exploring the energy landscapes of molecular recognition by a genetic algorithm : analysis of the requirements for robust docking of HIV-1 protease and FKBP-12 protein complexes. Proteins: Struct. Funct. Genet. 25: 342-353, 1996. PUBMED. Abstract.

ABSTRACT: Energy landscapes of molecular recognition are explored by performing “semi-rigid” docking of FK-506 and rapamycin with the Fukisawa binding protein (FKBP-12), and flexible docking simulations of the Ro-31-8959 and AG-1284 inhibitors with HIV-1 protease by a genetic algorithm. The requirements of a molecular recognition model to meet thermodynamic and kinetic criteria of ligand-protein docking simultaneously are investigated using a family of simple molecular recognition energy functions. The critical factor that determines the success rate in predicting the structure of ligand-protein complexes is found to be the roughness of the binding energy landscape, in accordance with a minimal frustration principle. The results suggest that further progress in structure prediction of ligand-protein complexes can be achieved by designing molecular recognition energy functions that generate binding landscapes with reduced frustration.

G. Verkhivker. Empirical free energy calculations of ligand-protein crystallographic complexes. II. Knowledge-based ligand-protein interaction potentials applied to the thermodynamic analysis of hydrophobic mutations. In “Pacific Symposium on Biocomputing-96”. World Scientific, Singapore, p. 638-652, 1996. PUBMED. Abstract.

ABSTRACT: Empirical free energy calculations of HIV-1 protease crystallographic complexes based on the developed knowledge-based ligand-protein interaction potentials have enabled a detailed thermodynamic analysis. Binding free energies are estimated within an empirical model that postulates that hydrophobic effect, mean field ligand-protein interaction potentials and conformational entropy changes are the dominant forces that determine complex formation. To provide a quantitative framework of the binding thermodynamics contributions the derived knowledge-based potentials have been linked with the hydrophobicity and conformational entropy scales originally developed to explain protein stability. The comparative analysis of studied inhibitors provides reasonable estimates of distinctions in their binding affinity with HIV-1 protease and gives insight into the nature of the binding determinants. The binding free energy changes upon a simple hydrophobic mutation Ile -> Val in the JG-365, MVT-101 and U75875 inhibitors of HIV-1 protease have been evaluated within a model that includes the effects of solvation, cavity formation, conformational entropy and mean field ligand-protein interactions. In general, free energy changes associated with a particular perturbation of a system can not be rigorously decomposed into separate terms from first principles. We explored the relationships between the changes in hydrophobic contributions and mean field ligand-protein interaction energies in the context of a totally buried and dense area of the binding site. We assume, therefore, that these simple hydrophobic deletions would not induce noticeable conformational changes in the enzyme and can be interpreted with some confidence in the framework of the model. The analysis has revealed the decisive effect of the energetics of ligand-protein interactions on the estimated free energy changes.


P. Rejto, G. Verkhivker, D.K. Gehlhaar, S.T. Freer. New trends in computational structure prediction of ligand-protein complexes for receptor--based drug design. In “Computer Simulations of Biomolecular Systems” vol. 3 , p. 451-465, Edited by W. van Gunsteren, ESCOM Science, Kluwer, Publishers B.V. Netherlands, 1995. Abstract.

ABSTRACT: A number of challenging computational problems arise in the field of structure-based drug design, including the estimation of ligand binding affinity and the de novo design of novel ligands. An important step toward solutions of these problems is the consistent and rapid prediction of the thermodynamically most favorable structure of a ligand—protein complex from the three-dimensional structures of its unbound ligand and protein components. This fundamental problem in molecular recognition is commonly known as the docking problem [1–3]. To solve this problem, two distinct conditions must be satisfied. The first is a thermodynamic requirement: the energy function used to describe ligand—protein binding must have the crystal structure of ligand—protein complexes as its global energy minimum. The second is a kinetic requirement: it must be possible to locate consistently and rapidly the global energy minimum on the ligand—protein binding energy landscape. While the first condition is necessary for successful structure prediction, it is by no means sufficient. Without kinetic accessibility, the global minimum cannot be reached during docking simulations, and computational structure prediction will fail. Here we review approaches to address both the kinetic and thermodynamic aspects of the docking problem.

D.K. Gehlhaar, G. Verkhivker, P. Rejto, C. Sherman, D. Fogel, L. Fogel, S.T. Freer. Molecular recognition of the inhibitor AG-1343 by HIV-1 protease : conformationally flexible docking by evolutionary programming. Chem. Biol. 2: 317-324, 1995. PUBMED. Abstract.

ABSTRACT: An important prerequisite for computational structure-based drug design is prediction of the structures of ligand-protein complexes that have not yet been experimentally determined by X-ray crystallography or NMR. For this task, docking of rigid ligands is inadequate because it assumes knowledge of the conformation of the bound ligand. Docking of flexible ligands would be desirable, but requires one to search an enormous conformational space. We set out to develop a strategy for flexible docking by, combining a simple model of ligand-protein interactions for molecular recognition with an evolutionary programming search technique.

G. Verkhivker, K. Appelt, S.T. Freer, Villafranca, J.E. Empirical free energy calculations of ligand-protein crystallographic complexes. I. Knowledge-based ligand-protein interaction potentials applied to the prediction of HIV-1 protease binding affinity. Protein Eng. 8 (7): 677-691, 1995. PUBMED. Abstract.

ABSTRACT: The steadily increasing number of high-resolution human immunodeficiency virus (HIV) 1 protease complexes has been the impetus for the elaboration of knowledge-based mean field ligand-protein interaction potentials. These potentials have been linked with the hydrophobicity and conformational entropy scales developed originally to explain protein folding and stability. Empirical free energy calculations of a diverse set of HIV-1 protease crystallographic complexes have enabled a detailed analysis of binding thermodynamics. The thermodynamic consequences of conformational changes that HIV-1 protease undergoes upon binding to all inhibitors, and a substantial concomitant loss of conformational entropy by the part of HIV-1 protease that forms the ligand-protein interface, have been examined. The quantitative breakdown of the entropy-driven changes occurring during ligand-protein association, such as the hydrophobic contribution, the conformational entropy term and the entropy loss due to a reduction of rotational and translationsal degrees of freedom, of a system composed of ligand, protein and crystallographic water molecules at the ligand-protein interface has been carried out The proposed approach provides reasonable estimates of distinctions in binding affinity and gives an insight into the nature of enthalpy-entropy compensation factors detected in the binding process.

G. Verkhivker, P. Rejto, D.K. Gehlhaar, S.T. Freer. Computer-aided structure prediction of ligand-protein complexes : exploring the energy landscapes of molecular recognition with HIV-1 protease. International Antiviral News 3: 146-147, 1995. Abstract.


R. Elber, A. Roitberg, C. Simmerling, R. Goldstein, H. Li, G. Verkhivker, C. Keasar, J. Zhang, A. Ulitsky. MOIL: A program for simulations of macromolecules. Comput. Phys. Commun. 91(1-3): 159-189, 1995. Abstract.

ABSTRACT: A package of computer programs for molecular dynamics simulations-MOIL-is described. A flexible data structure enables the study of macromolecules with potentials consistent with the AMBER/OPLS force field. The supplied parameter set has proteins in mind. In addition to ‘wide spread’ applications such as energy, energy minimization, normal modes, dynamics and free energy calculations code is also provided to pursue less common applications. This includes reaction path calculations (in condensed phases), uses of the mean field approach for enhanced sampling (LES-locally enhanced sampling) and calculations of curve crossing using the Landau-Zener model. A brief review of the overall program is provided. A few modules are discussed in considerable detail.

G. Verkhivker. Empirical free energy calculations of ligand-protein crystallographic complexes. Application of knowledge-based interaction potentials to prediction of binding affinity of HIV-1 protease complexes. In “QSAR and Molecular Modeling: Concepts, Computational Tools and Biological Applications.” Prous Publishers, p. 619-621, 1995. Abstract.


G. Verkhivker. Empirical free energy calculations of HIV-1 protease complexes. Mean field ligand-protein interaction potentials applied to prediction of binding affinity of diol-containing inhibitors. In “Perspectives on Protein Engineering”. Mayflower Worldwide Ltd., Oxford, p. 261-265, 1995. Abstract.


D.K. Gehlhaar, G. Verkhivker, P. Rejto, D. Fogel, L. Fogel, S.T. Freer. Docking of flexible small molecules into protein active site through evolutionary programming. In Evolutionary Programming , MIT Press, Cambridge, p. 615-627, 1995. Abstract.


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