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The COVID-19 pandemic continues to pose a substantial threat to human lives and is likely to do so for years to come. Despite the availability of vaccines, searching for efficient small-molecule drugs that are widely available, including in low- and middle-income countries, is an ongoing challenge. In this work, we report the results of a community effort, the “Billion molecules against Covid-19 challenge”, to identify small-molecule inhibitors against SARS-CoV-2 or relevant human receptors. Participating teams used a wide variety of computational methods to screen a minimum of 1 billion virtual molecules against 6 protein targets. Overall, 31 teams participated, and they suggested a total of 639,024 potentially active molecules, which were subsequently ranked to find ‘consensus compounds’. The organizing team coordinated with various contract research organizations (CROs) and collaborating institutions to synthesize and test 878 compounds for activity against proteases (Nsp5, Nsp3, TMPRSS2), nucleocapsid N, RdRP (Nsp12 domain), and (alpha) spike protein S. Overall, 27 potential inhibitors were experimentally confirmed by binding-, cleavage-, and/or viral suppression assays and are presented here. All results are freely available and can be taken further downstream without IP restrictions. Overall, we show the effectiveness of computational techniques, community efforts, and communication across research fields (i.e., protein expression and crystallography, in silico modeling, synthesis and biological assays) to accelerate the early phases of drug discovery.

The protein-ligand residence time, τ, influences molecular function in biological networks and has been recognized as an important determinant of drug efficacy. To predict τ, computational methods must overcome the problem that τ often exceeds the timescales accessible to conventional molecular dynamics (MD) simulation. Here, we apply the τ-Random Acceleration Molecular Dynamics (τRAMD) method to a set of kinetically characterized complexes of T4 lysozyme mutants with small, engineered binding cavities. τRAMD yields relative ligand dissociation rates in good accordance with experiments across this diverse set of complexes that differ with regard to measurement temperature, ligand identity, protein mutation and binding cavity. τRAMD thereby allows a comprehensive characterization of the ligand egress routes and determinants of τ. Although ligand dissociation by multiple egress routes is observed, we find that egress via the predominant route determines the value of τ. We also find that the presence of a greater number of metastable states along egress pathways leads to slower protein-ligand dissociation. These physical insights could be exploited in the rational optimization of the kinetic properties of drug candidates., Graphical abstract Image 1, Highlights • Relative residence times are computed for T4 lysozyme mutant-ligand complexes. • τ-Random Acceleration Molecular Dynamics provide efficient sampling of unbinding. • Computed dissociation rates show good agreement with all available measured values. • Ligand egress via the predominant route determines the value of the residence time. • The presence of metastable states along egress pathways slows down dissociation.

There is a growing appreciation of the importance of drug-target binding kinetics for lead optimization. For G protein-coupled receptors (GPCRs), which mediate signaling over a wide range of timescales, the drug dissociation rate is often a better predictor of in vivo efficacy than binding affinity, although it is more challenging to compute. Here, we assess the ability of the τ-Random Acceleration Molecular Dynamics (τRAMD) approach to reproduce relative residence times and reveal dissociation mechanisms and the effects of allosteric modulation for two important membrane-embedded drug targets: the β2-adrenergic receptor and the muscarinic acetylcholine receptor M2. The dissociation mechanisms observed in the relatively short RAMD simulations (in which molecular dynamics (MD) simulations are performed using an additional force with an adaptively assigned random orientation applied to the ligand) are in general agreement with much more computationally intensive conventional MD and metadynamics simulations. Remarkably, although decreasing the magnitude of the random force generally reduces the number of egress routes observed, the ranking of ligands by dissociation rate is hardly affected and agrees well with experiment. The simulations also reproduce changes in residence time due to allosteric modulation and reveal associated changes in ligand dissociation pathways.TABLE OF CONTENTS GRAPHIC

The binding kinetic properties of potential drugs may significantly influence their subsequent clinical efficacy. Predictions of these properties based on computer simulations provide a useful alternative to their expensive and time-demanding experimental counterparts, even at an early drug discovery stage.Herein, we perform Scaled Molecular Dynamics (ScaledMD) simulations on a set of 27 ligands of HSP90 belonging to more than 7 chemical series in order to estimate their relative residence time. We introduce two new techniques for the analysis and the classification of the simulated unbinding trajectories. The first technique, which helps in estimating the limits of the free energy well around the bound state and the second one, based on a new contact map fingerprint, allows the description and the comparison of the paths that lead to unbinding.Using these analyses, we find that ScaledMD’s relative residence time generally enables the identification of the slowest unbinders. We propose an explanation for the underestimation of the residence times of a subset of compounds and we investigate how the biasing in ScaledMD can affect the mechanistic insights that can be gained from the simulations.

There is a growing appreciation of the importance of drug-target binding kinetics for lead optimization. For G protein-coupled receptors (GPCRs), which mediate signaling over a wide range of time scales, the drug dissociation rate is often a better predictor of in vivo efficacy than binding affinity, although it is more challenging to compute. Here, we assess the ability of the τ-Random Acceleration Molecular Dynamics (τRAMD) approach to reproduce relative residence times and reveal dissociation mechanisms and the effects of allosteric modulation for two important membrane-embedded drug targets: the β2-adrenergic receptor and the muscarinic acetylcholine receptor M2. The dissociation mechanisms observed in the relatively short RAMD simulations (in which molecular dynamics (MD) simulations are performed using an additional force with an adaptively assigned random orientation applied to the ligand) are in general agreement with much more computationally intensive conventional MD and metadynamics simulations. Remarkably, although decreasing the magnitude of the random force generally reduces the number of egress routes observed, the ranking of ligands by dissociation rate is hardly affected and agrees well with experiment. The simulations also reproduce changes in residence time due to allosteric modulation and reveal associated changes in ligand dissociation pathways.

Simulations of macromolecular diffusion and adsorption in confined environments can offer valuable mechanistic insights into numerous biophysical processes. In order to model solutes at atomic detail on relevant time scales, Brownian dynamics simulations can be carried out with the approximation of rigid body solutes moving through a continuum solvent. This allows the precomputation of interaction potential grids for the solutes, thereby allowing the computationally efficient calculation of forces. However, hydrodynamic and long-range electrostatic interactions cannot be fully treated with grid-based approaches alone. Here, we develop a treatment of both hydrodynamic and electrostatic interactions to include the presence of surfaces by modeling grid-based and long-range interactions. We describe its application to simulate the self-association and many-molecule adsorption of the well-characterized protein hen egg-white lysozyme to mica-like and silica-like surfaces. We find that the computational model can recover a number of experimental observables of the adsorption process and provide insights into their determinants. The computational model is implemented in the Simulation of Diffusional Association (SDA) software package.

The SARS-CoV-2 coronavirus outbreak continues to spread at a rapid rate worldwide. The main protease (Mpro) is an attractive target for anti-COVID-19 agents. Unfortunately, unexpected difficulties have been encountered in the design of specific inhibitors. Here, by analyzing an ensemble of ~30,000 SARS-CoV-2 Mpro conformations from crystallographic studies and molecular simulations, we show that small structural variations in the binding site dramatically impact ligand binding properties. Hence, traditional druggability indices fail to adequately discriminate between highly and poorly druggable conformations of the binding site. By performing ~200 virtual screenings of compound libraries on selected protein structures, we redefine the protein’s druggability as the consensus chemical space arising from the multiple conformations of the binding site formed upon ligand binding. This procedure revealed a unique SARS-CoV-2 Mpro blueprint that led to a definition of a specific structure-based pharmacophore. The latter explains the poor transferability of potent SARS-CoV Mpro inhibitors to SARS-CoV-2 Mpro, despite the identical sequences of the active sites. Importantly, application of the pharmacophore predicted novel high affinity inhibitors of SARS-CoV-2 Mpro, that were validated by in vitro assays performed here and by a newly solved X-ray crystal structure. These results provide a strong basis for effective rational drug design campaigns against SARS-CoV-2 Mpro and a new computational approach to screen protein targets with malleable binding sites.

There is increasing evidence of a significant correlation between prolonged drug-target residence time and increased drug efficacy. Here, we report a structural rationale for kinetic selectivity between two closely related kinases: focal adhesion kinase (FAK) and proline-rich tyrosine kinase 2 (PYK2). We found that slowly dissociating FAK inhibitors induce helical structure at the DFG motif of FAK but not PYK2. Binding kinetic data, high-resolution structures and mutagenesis data support the role of hydrophobic interactions of inhibitors with the DFG-helical region, providing a structural rationale for slow dissociation rates from FAK and kinetic selectivity over PYK2. Our experimental data correlate well with computed relative residence times from molecular simulations, supporting a feasible strategy for rationally optimizing ligand residence times. We suggest that the interplay between the protein structural mobility and ligand-induced effects is a key regulator of the kinetic selectivity of inhibitors of FAK versus PYK2.

There is increasing evidence of a significant correlation between prolonged drug-target residence time and increased drug efficacy. Here, we report a structural rational for kinetic selectivity between two closely related kinases: Focal Adhesion Kinase (FAK) and Proline-rich Tyrosine Kinase 2 (PYK2). We found that slow off-rate FAK inhibitors induce helical structure at the DFG motif of FAK but not PYK2. Binding kinetic data, high resolution structures and mutagenesis data support the role of hydrophobic interactions of inhibitors with the DFG helical region providing a structural rational for slow dissociation rates from FAK and kinetic selectivity over PYK2. Our experimental data correlated well with computed relative residence times from molecular simulations providing a feasible strategy for rationally optimizing ligand residence times. We suggest that the interplay between the protein structural mobility and ligand-induced effects is a key regulator of the kinetic selectivity of inhibitors of FAK versus PYK2.

The recent and growing evidence that the efficacy of a drug can be correlated to target binding kinetics has seeded the development of a multitude of novel methods aimed at computing rate constants for receptor-ligand binding processes, as well as gaining an understanding of the binding and unbinding pathways and the determinants of structure-kinetic relationships. These new approaches include various types of enhanced sampling molecular dynamics simulations and the combination of energy-based models with chemometric analysis. We assess these approaches in the light of the varying levels of complexity of protein-ligand binding processes.

The TRAnsient Pockets in Proteins (TRAPP) webserver provides an automated workflow that allows users to explore the dynamics of a protein binding site and to detect pockets or sub-pockets that may transiently open due to protein internal motion. These transient or cryptic sub-pockets may be of interest in the design and optimization of small molecular inhibitors for a protein target of interest. The TRAPP workflow consists of the following three modules: (i) TRAPP structure— generation of an ensemble of structures using one or more of four possible molecular simulation methods; (ii) TRAPP analysis—superposition and clustering of the binding site conformations either in an ensemble of structures generated in step (i) or in PDB structures or trajectories uploaded by the user; and (iii) TRAPP pocket—detection, analysis, and visualization of the binding pocket dynamics and characteristics, such as volume, solvent-exposed area or properties of surrounding residues. A standard sequence conservation score per residue or a differential score per residue, for comparing on- and off-targets, can be calculated and displayed on the binding pocket for an uploaded multiple sequence alignment file, and known protein sequence annotations can be displayed simultaneously. The TRAPP webserver is freely available at http://trapp.h-its.org.

The addition of three N-terminal histidines to β-lactamase inhibitor protein was shown experimentally to increase its binding potency to an Au(111) surface substantially but the binding mechanism was not resolved. Here, we propose a complete adsorption mechanism for this fusion protein by means of a multi-scale simulation approach and free energy calculations. We find that adsorption is a three-step process: (i) recognition of the surface predominantly by the histidine fusion peptide and formation of an encounter complex facilitated by a reduced dielectric screening of water in the interfacial region, (ii) adsorption of the protein on the surface and adoption of a specific binding orientation, and (iii) adaptation of the protein structure on the metal surface accompanied by induced fit. We anticipate that the mechanistic features of protein adsorption to an Au(111) surface revealed here can be extended to other inorganic surfaces and proteins and will therefore aid the design of specific protein-surface interactions.

Drug-target residence time (τ), one of the main determinants of drug efficacy, remains highly challenging to predict computationally and, therefore, is usually not considered in the early stages of drug design. Here, we present an efficient computational method, τ-random acceleration molecular dynamics (τRAMD), for the ranking of drug candidates by their residence time and obtaining insights into ligand-target dissociation mechanisms. We assessed τRAMD on a data set of 70 diverse drug-like ligands of the N-terminal domain of HSP90α, a pharmaceutically important target with a highly flexible binding site, obtaining computed relative residence times with an accuracy of about 2.3τ for 78% of the compounds and less than 2.0τ within congeneric series. Analysis of dissociation trajectories reveals features that affect ligand unbinding rates, including transient polar interactions and steric hindrance. These results suggest that τRAMD will be widely applicable as a computationally efficient aid to improving drug residence times during lead optimization.

Structure-based drug design has often been restricted by the rather static picture of protein–ligand complexes presented by crystal structures, despite the widely accepted importance of protein flexibility in biomolecular recognition. Here we report a detailed experimental and computational study of the drug target, human heat shock protein 90, to explore the contribution of protein dynamics to the binding thermodynamics and kinetics of drug-like compounds. We observe that their binding properties depend on whether the protein has a loop or a helical conformation in the binding site of the ligand-bound state. Compounds bound to the helical conformation display slow association and dissociation rates, high-affinity and high cellular efficacy, and predominantly entropically driven binding. An important entropic contribution comes from the greater flexibility of the helical relative to the loop conformation in the ligand-bound state. This unusual mechanism suggests increasing target flexibility in the bound state by ligand design as a new strategy for drug discovery., An understanding of the dynamics of drug binding and unbinding processes is important for drug discovery. Here, the authors give insights into the binding mechanism of small drug-like molecules to human Hsp90 by combining thermodynamics and kinetics studies as well as molecular dynamics simulations.

The simulation of diffusional association (SDA) Brownian dynamics software package has been widely used in the study of biomacromolecular association. Initially developed to calculate bimolecular protein–protein association rate constants, it has since been extended to study electron transfer rates, to predict the structures of biomacromolecular complexes, to investigate the adsorption of proteins to inorganic surfaces, and to simulate the dynamics of large systems containing many biomacromolecular solutes, allowing the study of concentration‐dependent effects. These extensions have led to a number of divergent versions of the software. In this article, we report the development of the latest version of the software (SDA 7). This release was developed to consolidate the existing codes into a single framework, while improving the parallelization of the code to better exploit modern multicore shared memory computer architectures. It is built using a modular object‐oriented programming scheme, to allow for easy maintenance and extension of the software, and includes new features, such as adding flexible solute representations. We discuss a number of application examples, which describe some of the methods available in the release, and provide benchmarking data to demonstrate the parallel performance. © 2015 The Authors. Journal of Computational Chemistry Published by Wiley Periodicals, Inc.

A considerable number of approved drugs show non-equilibrium binding characteristics, emphasizing the potential role of drug residence times for in vivo efficacy. Therefore, a detailed understanding of the kinetics of association and dissociation of a target-ligand complex might provide crucial insight into the molecular mechanism-of-action of a compound. This deeper understanding will help to improve decision making in drug discovery, thus leading to a better selection of interesting compounds to be profiled further. In this review, we highlight the contributions of the Kinetics for Drug Discovery (K4DD) Consortium, which targets major open questions related to binding kinetics in an industry-driven public-private partnership.

Simulations of the long-time scale motions of a ligand binding pocket in a protein may open up new perspectives for the design of compounds with steric or chemical properties differing from those of known binders. However, slow motions of proteins are difficult to access using standard molecular dynamics (MD) simulations and are thus usually neglected in computational drug design. Here, we introduce two nonequilibrium MD approaches to identify conformational changes of a binding site and detect transient pockets associated with these motions. The methods proposed are based on the rotamerically induced perturbation (RIP) MD approach, which employs perturbation of side-chain torsional motion for initiating large-scale protein movement. The first approach, Langevin-RIP (L-RIP), entails a series of short Langevin MD simulations, each starting with perturbation of one of the side-chains lining the binding site of interest. L-RIP provides extensive sampling of conformational changes of the binding site. In less than 1 ns of MD simulation with L-RIP, we observed distortions of the α-helix in the ATP binding site of HSP90 and flipping of the DFG loop in Src kinase. In the second approach, RIPlig, a perturbation is applied to a pseudoligand placed in different parts of a binding pocket, which enables flexible regions of the binding site to be identified in a small number of 10 ps MD simulations. The methods were evaluated for four test proteins displaying different types and degrees of binding site flexibility. Both methods reveal all transient pocket regions in less than a total of 10 ns of simulations, even though many of these regions remained closed in 100 ns conventional MD. The proposed methods provide computationally efficient tools to explore binding site flexibility and can aid in the functional characterization of protein pockets, and the identification of transient pockets for ligand design.

The dynamics of protein binding pockets are crucial for their interaction specificity. Structural flexibility allows proteins to adapt to their individual molecular binding partners and facilitates the binding process. This implies the necessity to consider protein internal motion in determining and predicting binding properties and in designing new binders. Although accounting for protein dynamics presents a challenge for computational approaches, it expands the structural and physicochemical space for compound design and thus offers the prospect of improved binding specificity and selectivity. A cavity on the surface or in the interior of a protein that possesses suitable properties for binding a ligand is usually referred to as a binding pocket. The set of amino acid residues around a binding pocket determines its physicochemical characteristics and, together with its shape and location in a protein, defines its functionality. Residues outside the binding site can also have a long-range effect on the properties of the binding pocket. Cavities with similar functionalities are often conserved across protein families. For example, enzyme active sites are usually concave surfaces that present amino acid residues in a suitable configuration for binding low molecular weight compounds. Macromolecular binding pockets, on the other hand, are located on the protein surface and are often shallower. The mobility of proteins allows the opening, closing, and adaptation of binding pockets to regulate binding processes and specific protein functionalities. For example, channels and tunnels can exist permanently or transiently to transport compounds to and from a binding site. The influence of protein flexibility on binding pockets can vary from small changes to an already existent pocket to the formation of a completely new pocket. Here, we review recent developments in computational methods to detect and define binding pockets and to study pocket dynamics. We introduce five different classes of protein pocket dynamics: (1) appearance/disappearance of a subpocket in an existing pocket; (2) appearance/disappearance of an adjacent pocket on the protein surface in the direct vicinity of an already existing pocket; (3) pocket breathing, which may be caused by side-chain fluctuations or backbone or interdomain vibrational motion; (4) opening/closing of a channel or tunnel, connecting a pocket inside the protein with solvent, including lid motion; and (5) the appearance/disappearance of an allosteric pocket at a site on a protein distinct from an already existing pocket with binding of a ligand to the allosteric binding site affecting the original pocket. We suggest that the class of pocket dynamics, as well as the type and extent of protein motion affecting the binding pocket, should be factors considered in choosing the most appropriate computational approach to study a given binding pocket. Furthermore, we examine the relationship between pocket dynamics classes and induced fit, conformational selection, and gating models of ligand binding on binding kinetics and thermodynamics. We discuss the implications of protein binding pocket dynamics for drug design and conclude with potential future directions for computational analysis of protein binding pocket dynamics.

Understanding protein–inorganic surface interactions is central to the rational design of new tools in biomaterial sciences, nanobiotechnology and nanomedicine. Although a significant amount of experimental research on protein adsorption onto solid substrates has been reported, many aspects of the recognition and interaction mechanisms of biomolecules and inorganic surfaces are still unclear. Theoretical modeling and simulations provide complementary approaches for experimental studies, and they have been applied for exploring protein–surface binding mechanisms, the determinants of binding specificity towards different surfaces, as well as the thermodynamics and kinetics of adsorption. Although the general computational approaches employed to study the dynamics of proteins and materials are similar, the models and force-fields (FFs) used for describing the physical properties and interactions of material surfaces and biological molecules differ. In particular, FF and water models designed for use in biomolecular simulations are often not directly transferable to surface simulations and vice versa. The adsorption events span a wide range of time- and length-scales that vary from nanoseconds to days, and from nanometers to micrometers, respectively, rendering the use of multi-scale approaches unavoidable. Further, changes in the atomic structure of material surfaces that can lead to surface reconstruction, and in the structure of proteins that can result in complete denaturation of the adsorbed molecules, can create many intermediate structural and energetic states that complicate sampling. In this review, we address the challenges posed to theoretical and computational methods in achieving accurate descriptions of the physical, chemical and mechanical properties of protein-surface systems. In this context, we discuss the applicability of different modeling and simulation techniques ranging from quantum mechanics through all-atom molecular mechanics to coarse-grained approaches. We examine uses of different sampling methods, as well as free energy calculations. Furthermore, we review computational studies of protein–surface interactions and discuss the successes and limitations of current approaches.

The Dynathor project aims at understanding the interaction of cytochrome P450 (CYP, P450) enzymes and their redox partner, cytochrome P450 reductase (CPR), in a phospholipid bilayer. Through simulation studies on the HLRS CRAY systems (initially XE6, later on XC40), we investigated the interactions of models of membrane-bound P450s (CYP51 and CYP1A1) and CPR. A model of membrane-bound T. brucei CYP51 and the human CPR was successfully built and simulated for 217.5 ns. A model of human CYP1A1 and the human CPR in a phospholipid bilayer was also built and is being simulated. These models can be used as starting points to understand the selectivity of the interactions of CYPs with CPR in the native membrane-bound forms, and thus may aid drug discovery projects.

Fluorescent labels are often attached to proteins to monitor binding and adsorption processes. Docking simulations for native hen egg white lysozyme (HEWL) and HEWL labeled with fluorescein isothiocyanate show that these adsorb differently on charged surfaces. Attachment of even a small label can significantly change the interaction properties of a protein. Thus, the results of experiments with fluorescently labeled proteins should be interpreted by modeling the structures and computing the interaction properties of both labeled and unlabeled species.

Protein structural flexibility plays a critical role in receptor–ligand binding processes and should be considered in computational drug design. However, the treatment of protein conformational changes is still a major challenge because it is associated with a large increase in the conformational space that needs to be sampled and requires highly accurate scoring functions that incorporate the receptor reorganization energy. A number of different approaches have been proposed recently to address this problem. Most of them have been shown to be successful in reproducing the correct docking pose of known ligands, but their benefit regarding enrichment, affinity prediction, and screening of large molecular libraries is less clear. Here, we review current methodologies to treat receptor conformational changes in structure-based docking procedures, and show their impact on the accuracy of docking and scoring. We also discuss pitfalls and limitations of state-of-the-art flexible-receptor docking strategies and perspectives for their improvement. © 2011 John Wiley & Sons, Ltd. WIREs Comput Mol Sci 2011 1 298-314 DOI: 10.1002/wcms.29

Interactions of peptides and proteins with inorganic surfaces are important to both natural and artificial systems; however, a detailed understanding of such interactions is lacking. In this study, we applied new approaches to quantitatively measure the binding of amino acids and proteins to gold surfaces. Real-time surface plasmon resonance (SPR) measurements showed that TEM1-β-lactamase inhibitor protein (BLIP) interacts only weakly with Au nanoparticles (NPs). However, fusion of three histidine residues to BLIP (3H-BLIP) resulted in a significant increase in the binding to the Au NPs, which further increased when the histidine tail was extended to six histidines (6H-BLIP). Further increasing the number of His residues had no effect on the binding. A parallel study using continuous (111)-textured Au surfaces and single-crystalline, (111)-oriented, Au islands by ellipsometry, FTIR, and localized surface plasmon resonance (LSPR) spectroscopy further confirmed the results, validating the broad applicability of Au NPs as model surfaces. Evaluating the binding of all other natural amino acid homotripeptides fused to BLIP (except Cys and Pro) showed that aromatic and positively-charged residues bind preferentially to Au with respect to small aliphatic and negatively charged residues, and that the rate of association is related to the potency of binding. The binding of all fusions was irreversible. These findings were substantiated by SPR measurements of synthesized, free, soluble tripeptides using Au-NP-modified SPR chips. Here, however, the binding was reversible allowing for determination of binding affinities that correlate with the binding potencies of the related BLIP fusions. Competition assays performed between 3H-BLIP and the histidine tripeptide (3 His) suggest that Au binding residues promote the adsorption of proteins on the surface, and by this facilitate the irreversible interaction of the polypeptide chain with Au. The binding of amino acids to Au was simulated by using a continuum solvent model, showing agreement with the experimental values. These results, together with the observed binding potencies and kinetics of the BLIP fusions and free peptides, suggest a binding mechanism that is markedly different from biological protein-protein interactions.

In order to study protein-inorganic surface association processes, we have developed a physics-based energy model, the ProMetCS model, which describes protein-surface interactions at the atomistic level while treating the solvent as a continuum. Here, we present an approach to modeling the interaction of a protein with an atomically flat Au(111) surface in an aqueous solvent. Protein-gold interactions are modeled as the sum of van der Waals, weak chemisorption, and electrostatic interactions, as well as the change in free energy due to partial desolvation of the protein and the metal surface upon association. This desolvation energy includes the effects of water-protein, water-surface, and water-water interactions and has been parametrized using molecular dynamics (MD) simulations of water molecules and a test atom at a gold-water interface. The proposed procedure for computing the energy terms is mostly grid-based and is therefore efficient for application to long-time simulations of protein binding processes. The approach was tested for capped amino acid residues whose potentials of mean force for binding to a gold surface were computed and compared with those obtained previously in MD simulations with water treated explicitly. Calculations show good quantitative agreement with the results from MD simulations for all but one amino acid (Trp), as well as correspondence with available experimental data on the adhesion properties of amino acids.

While modern docking methods often predict accurate binding modes, affinity calculations remain challenging and enrichment rates of in silico screening methods unsatisfactory. Inadequate treatment of induced fit effects is one major shortcoming of existing in silico screening methods. Here we investigate enrichment rates of rigid-, soft- and flexible-receptor models for 12 diverse receptors using libraries containing up to 13000 molecules. For the rigid-receptor model, we observed high enrichment (EF120) only for four target proteins. A soft-receptor model showed improved docking rates at the expense of reduced enrichment rates. A flexible side-chain model with flexible dihedral angles for up to 12 amino acids (3-8 flexible side chains) increased both binding propensity and enrichment rates: EF1 values increased by approximately 35% on average with respect to rigid docking. We find on average 4 known ligands in the top 10 molecules in the rank-ordered databases for the receptors investigated.

A theoretical study of the photoinduced C-H bond cleavage in H 2 CO adsorbed on Ag(111) surface is carried out by employing an ab initio embedding approach and multireference configuration interaction method. Pathways for one- and two-step fragmentation into CO + 2H are investigated as well as adsorption properties of the H and HCO products. The π* electron-attachment state, H 2 CO -(a) , formed due to photoinduced electron transfer from the surface to an adsorbate, serves as intermediate for the dissociation process. An effective reaction pathway includes initial nuclear relaxation of the H 2 CO -(a) anion followed by electron detachment and subsequent dissociation of the neutral H 2 CO (a) molecule. The present calculations also show that, in contrast to gaseous H 2 CO, cleavage of the C-H bond in adsorbed H 2 CO needs higher excitation energy than the C-O bond. The corresponding energy difference is obtained to be about 1.6 eV.

The chemisorption of various atoms (C, N, O, Cl) and molecular fragments (OH, NH, CH, NH 2 , CH 2 ) on the Ag(1 1 1) surface has been studied by employing the embedded cluster and multireference single- and double-excitation configuration interaction (MRD-CI) methods. Ground and excited states of the cluster–adsorbate systems have been computed and molecular orbitals (MOs) as well as electronic charge density distributions and Mulliken populations have been analyzed in order to extract general trends in chemisorption properties for different adsorbates. It has been found that the adsorbate–surface bond is energetically most favorable when a maximum of two electrons of the metal are shared with a given adsorbate. As a result atomic/molecular fragments with less than six valence electrons (N, CH, C) retain some open shells upon adsorption, whereas oxygen as well as chlorine isovalent species form a singlet ground state on the surface. All species considered except for Cl have mainly covalent bonding character to the surface, with an electronic charge of up to 1.0 transferred to the adsorbate from the silver cluster. It has been shown that the ionicity of the bond is strongly correlated with the electron affinity of the adsorbed species. Binding energies, equilibrium geometry and adsorbate location on the cluster have been computed and compared with available experimental data. In addition, the characteristic properties of chemisorption on Ag(1 1 1) and Pt(1 1 1) surfaces have been compared.

We describe a spectroscopic study of the electron distribution functions (EDFs) in two types of electron cyclotron resonance (ECR) discharges at very low pressure: a discharge in a simple magnetic mirror trap (ECRD) and a discharge in a sheared minimum-B-trap used as ion source for multiply charged ions (ECRIS). The discharges were run in mixtures of helium and nitrogen at about 7?mPa. Special attention was paid to electrons with kinetic energies below 10?eV. Their contributions were attained by a quantitative analysis of the vibrational structures in the emission spectra of nitrogen, the analysis of processes of step-wise excitation or an analysis of the rotational populations of nitrogen. The models for evaluating the EDFs are discussed in detail. Besides collision processes in the volume of the discharge processes occurring at the chamber walls contribute significantly to the particle balance and are included in the model. In all cases considered low energy electrons contribute more than 90% to the electron population of the discharges. For every discharge EDFs are measured for two benchmark conditions at low and high discharge power. For the ECRIS other conditions are covered by a measurement of the plasma potential, which turned out to be below 30?V for the conditions considered. This low value is a good indicator for the presence of low energy electrons. The plasma potential was obtained from a retarding field analysis of the energy of ion beams extracted from the plasma.Besides the EDFs, our study yields insight into the important collision and wall processes in these low-pressure discharges, including the first observation of rotational cooling of desorbing N2 molecules in an ECRIS.

Potential energy curves for the X (1)Sigma(g) (+) ground state and Omega=0(u) (+), 1(u) valence states and dipole moments for the 0(u) (+), 1(u)-X transitions are obtained in an ab initio configuration interaction study of Cl(2) including spin-orbit coupling. In contrast to common assumptions, it is found that the B (3)Pi(0(+)u)-X transition moment strongly depends on internuclear distance, which has an important influence on the Cl(2) photodissociation. Computed energy curves and transition moments are employed to calculate the A, B, C

A procedure is developed to obtain pseudo-canonical localized molecular orbitals for use in ab initio multireference CI calculations of the electronic spectra of molecules adsorbed on the surfaces of large clusters of metal atoms. The Pt97CO system is employed as a test and potential curves are computed for a large number of its electronic states. The present method is able to accurately describe internally excited states of the adsorbed CO molecule without computing most of the charge-transfer states of lower energy which occur in the same MRD-CI secular equations. It is found that the potentials of the σ–π* states are repulsive along the Pt–C coordinate and hence that their transition energies from the ground state are much higher (11.4–11.6 eV) than for the isolated CO molecule. The corresponding π–π* states are all relatively strongly bound, however, similarly as for the ground state, with transitions to them occurring as much as 1 eV lower than when the Pt97 cluster is absent. This behavior can be traced to the fact that the Pt–C bonding orbital in the ground state has a large amount of CO sigma character, consistent with earlier calculations reported for the Pt7CO model system, whereas neither the π nor the π* MO is strongly affected by the approach of the metal cluster.

The structure of the Ω=1,2 states correlating with the F−(1S0)+Cl+(3PJ) ionic products and their emission are studied. Ab initio potential energy curves of ClF published recently and computed electronic dipole moments for parallel transitions between the Ω=1,2 ion pair and valence states, as reported in the present work, are used to calculate vibrational energies and emission spectra in the adiabatic and nonadiabatic approximations. It is shown that spectroscopic and emission properties of the D′2(3P2) state can be quite accurately described in the adiabatic approximation. On the contrary, the G1(3P1) and β1(3P2) states are nonadiabatically mixed due to the strong radial coupling caused by significant variation of the 3Σ− and 3Π Λ–S contributions, similar to that observed for the E0+(3P2) and f0+(3P0) states. Nonadiabatic calculations carried out for the G1(3P1) and β1(3P2) ion-pair states clearly demonstrate the influence of the radial coupling on the emission spectra, although do not reproduce quantitat...

Electronic structure and radiative characteristics of low-lying ion-pair states of Cl2 converging to the Cl+(3P, 1D)+Cl−(1S) limits are studied. Ab initio calculations of potential energy curves for the valence and ion-pair states and dipole moments for transitions between them are carried out employing the multireference single- and double-excitation configuration interaction (MRD-CI) method, including spin–orbit coupling. It is shown that the lowest two pairs of the Ω=0u+, 1u ion-pair states arise from an avoided crossing between the 3Σu− and 3Πu parent Λ−S states, which leads to notably anharmonic shapes of the corresponding potential curves and their mixed Λ−S nature. This causes significant radial coupling, resulting in the strongly perturbed character of the 0u+ and 1u states observed experimentally. In contrast, their gerade counterparts run parallel to one another and exhibit much less perturbation. Spectroscopic properties of the computed adiabatic curves are in very good agreement with the available experimental data. Dipole moments have been calculated for parallel ion-pair–valence state transitions and radiative lifetimes have been obtained for the adiabatic ion-pair states. A reanalysis of the experimental bound–free emission spectra from the D0u+(3P2) state [N. K. Bibinov et al., Chem. Phys. 254, 89 (2000)] is given.

Nonadiabatic calculations of vibrational energies and wave functions are carried out for the E(0+, 3P2) and f(0+, 3P0) ion-pair states of the ClF molecule. It is shown that strong radial coupling between these 0+ states is caused by a significant variation of their 3Σ− and 3Π Λ-S contributions with internuclear distance and results in vibrational energy shifts as well as changes in the corresponding adiabatic vibrational wave functions. Both resonance and nonresonance interactions between vibronic levels of these two adiabatic states are found to be important, but significant mixing of the adiabatic wave functions can occur only for the nearly resonant levels located around f,v=3; E,v=7 and f,v=8; E,v=13. Nonadiabatic interactions are found to be responsible for the appearance of long-wavelength maxima in the f,v=3,4 emission spectra that was the subject of the discrepancy between theoretical and experimental data discussed in the previous paper [A. B. Alekseyev, H.-P. Liebermann, R. J. Buenker, and D. B....

The dependencies of rate constant of the intramolecular I 2 ( E0 g + → M D0 u + ) approach-induced transition, M=He, Ar, I 2 , N 2 , CF 4 , on the vibrational v E , v D , rotational J E , J D numbers, energy gaps, and Franck–Condon factors of the combined levels have been studied at nearly single-collision conditions by the OODR method. It has been shown that the observed approach-induced intramolecular transitions (AIIT) are nonresonant, correspond to loss of 100–700 cm −1 or gain of 160 cm −1 energy. For M≠CF 4 their cross-sections are independent of initial J E ≈50–110 number and up to 60 (M=He) times less than maximum cross-section of the extremely long-range nearly resonant I 2 ( E ,v E ↔ I 2 ( X ) D ,v D ) AIIT [Chem. Phys. 242 (1999) 263]. The nonresonant transition corresponding to loss of up to 160 cm −1 energy was found out for M=I 2 , as well, but its cross-section is approximately nine times less than the maximum cross-section of the nearly resonant I 2 ( E ,v E ↔ I 2 ( X ) D ,v D ) processes. The u↔g and ΔΩ=0 propensity rules are valid in the I 2 ( E )+M→I 2 (ion-pair states) + M AIIT. The vibrational and rotational distributions of the D state levels depend on the M nature. The J E dependence of the AIIT rate constant in the M=CF 4 case has been found out. For J E =110 rate constant is close to that of resonance approach-induced one, and the single rovibronic v D , J D ≈110 level corresponding to loss of about 1290 cm −1 energy is populated. It has been shown that the data observed in this work and Chem. Phys. 242 (1999) 263 can be qualitatively explained in the framework of model of collision (approach) with large impact parameter.

An ab initio configuration interaction (CI) study including spin-orbit coupling is carried out for the ground and low-lying excited states of the HI molecule by employing a relativistic effective core potential for the iodine atom. The computed spectroscopic constants for the X 1Σ+ ground and b 3ΠΩ Rydberg states are in good agreement with available experimental data, as are the vertical excitation energies for the repulsive a 3Π1, a 3Π0+, and A 1Π1 states of the A band. The a 3Π0+ state is found to possess a shallow minimum of 600 cm−1 depth outside the Franck–Condon region, at ≈5.1 a0. The electric-dipole moments have also been calculated for transitions from the ground to the A band states. Contrary to what is usually assumed, the a 3Π1, A 1Π1←X0+ transition moments are found to depend strongly on internuclear distance. Employing the computed potential energy and transition moment data, partial and total absorption spectra for the A band are calculated and the I* quantum yields, ΦI*(ν), are determined ...

Bound–bound 0 + u ( 3 P 2 )→ X 0 + g and bound-free 0 + u ( 3 P 2 )→(2,3,4)0 + g luminescence spectra of molecular chlorine have been measured in the 210–330 nm spectral range after OODR excitation. The relative dipole moment functions of the transitions as well as potential energy curves of the repulsive 0 + g states correlated with the Cl(2P3/2) + Cl(2P3/2), Cl(2P1/2) + Cl(2P3/2) and Cl(2P1/2) + Cl(2P1/2) dissociation limits have been determined for the first time. The functions of the 0 + u ( 3 P 2 ) – X 0 + g , 0 + u ( 3 P 2 ) – (3)0 + g and 0 + u ( 3 P 2 ) – (4)0 + g transition have unusual forms. Possible electronic configurations of the states combined in the optical transitions have been discussed.

An ab initio configuration interaction (CI) study including spin–orbit coupling is carried out for numerous valence and ion-pair states of the ClF molecule by employing relativistic effective core potentials. The computed spectroscopic constants are in good agreement with available experimental data for both valence and ion-pair states. The present calculations accurately reproduce the measured spin–orbit splittings for the first 3Π multiplet and confirm the recent corrected spectroscopic parameters for the A 3Π1 state [V. A. Alekseev, D. W. Setser, and J. Tellinghuisen, J. Mol. Spectrosc. 195, 162 (1999)]. The electronic structure of the six lowest ion-pair states of ClF which correlate to the Cl+(3P)+F−(1S) limit is analyzed in detail. It is shown that strong homogeneous perturbations of the E0+ and f0+, β1, and G1 states are mainly caused by an avoided crossing of the 3 3Π and 2 3 Σ− parent Λ–S states. The electric-dipole transition moments have also been calculated for transitions from the E and f ion...

The optical-optical double-resonance technique has been used for measurements of emission spectra from separate vibrational levels of the 1(3P2) state of ICl (v´ = 12 and 14) populated via the A 1 3 state. The electric dipole moment function of the A transition has been determined over the range of the internuclear distance of 0.29-0.39 nm by means of simulation of the emission spectra from the state.

The dependences of the I 2 ( E , v E ↔ I 2 ( X ) D , v D ) collision-induced transition rate constant on the vibrational vE, vD, rotational JD numbers, energy gaps, and Franck–Condon factors (FCF) of the combined levels have been studied. Selected rovibrational levels of the E state have been produced by optical–optical double resonance (OODR) excitation via the B0u+ state. Rovibronic levels of the D state populated in collision-induced intramolecular transitions (CIIT) in the nearly single-collision conditions have been identified. Rate constants of CIIT derived from the E→B and D→X emission spectra simulation have been determined. It has been shown that the u↔g, ΔΩ=0 and ΔJ≤3 propensity rules are valid in the I2(E)+I2(X) → I2(ion-pair states)+I2(X) process. Its cross-sections are giant ((1.1–3.3)×103 A2), and there is distinct correlation between them and energy gaps ΔE=f(Δv, ΔJ) of the combined rovibronic levels. The transitions between isoenergetic rovibronic levels are the most probable. There is no correlation between the cross-sections of transitions and FCF of the levels. An applicability of some models of CIIT to the processes under study has been discussed. It has been shown that they cannot explain the observed experimental data. It would be better to call the processes similar to the observed one as `approach-induced' to emphasize their extremely long-range character.