Protein-ligand interaction energies with dispersion corrected density functional theory and high-level wave function based methods

Aggregation-Induced Modulation of Ground and Excited State Photophysics of 5-(tert-Butyl)-2-Hydroxy-1,3-Isophthalaldehyde (5-tBHI)

5-(tert-Butyl)-2-hydroxy-1,3-isophthalaldehyde (5-tBHI) is a photochromic material susceptible to either excited state proton transfer or excited state intramolecular proton transfer, depending upon the solvent. However, it has also been found to aggregate in the presence of sodium dodecyl sulfate. In this current study, based on the steady-state and time-resolved spectroscopy, supported by crystallography, quantum chemical density functional theory calculation, and molecular dynamics (MD) simulation, we report on the aggregation of this potential single benzene-based emitter (SBBE) in neat solvents as well as solid phase to modulate its photophysics. It has been found that 5-tBHI forms mixed aggregates of different orders, owing to the presence of both enolic and tautomeric forms, to yield tunable emission, although the emission intensity is quenched. These findings suggest that the intramolecular hydrogen bonding of 5-tBHI not only limits intermolecular interactions but also promotes nonradiative deactivation pathways. Hence, designing and structural engineering, with a focus to suppressing intramolecular hydrogen bonding as well as increasing through space conjugation by replacing the aldehydic moieties with bulky aliphatic or aromatic ketonic groups, can be a plausible approach to yielding improved probes with tunable emission and higher fluorescence quantum yields.

A computational study of the reaction mechanism and stereospecificity of dihydropyrimidinase

Dihydropyrimidinase (DHPase) is a key enzyme in the pyrimidine pathway, the catabolic route for synthesis of β-amino acids. It catalyses the reversible conversion of 5,6-dihydrouracil (DHU) or 5,6-dihydrothymine (DHT) to the corresponding N-carbamoyl-β-amino acids. This enzyme has the potential to be used as a tool in the production of β-amino acids. Here, the reaction mechanism and origin of stereospecificity of DHPases from Saccharomyces kluyveri and Sinorhizobium meliloti CECT4114 were investigated and compared using a quantum mechanical cluster approach based on density functional theory. Two models of the enzyme active site were designed from the X-ray crystal structure of the native enzyme: a small cluster to characterize the mechanism and the stationary points and a large model to probe the stereospecificity and the role of stereo-gate-loop (SGL) residues. It is shown that a hydroxide ion first performs a nucleophilic attack on the substrate, followed by the abstraction of a proton by Asp358, which occurs concertedly with protonation of the ring nitrogen by the same residue. For the DHT substrate, the enzyme displays a preference for the L-configuration, in good agreement with experimental observation. Comparison of the reaction energetics of the two models reveals the importance of SGL residues in the stereospecificity of catalysis. The role of the conserved Tyr172 residue in transition-state stabilization is confirmed as the Tyr172Phe mutation increases the activation barrier of the reaction by ∼8 kcal mol^-1. A detailed understanding of the catalytic mechanism of the enzyme could offer insight for engineering in order to enhance its activity and substrate scope.

System truncation accelerates binding affinity calculations with the fragment molecular orbital method: A benchmark study

The fragment molecular orbital (FMO) method is a fast quantum-mechanical method that divides systems into pieces of fragments and performs ab initio calculations. The system truncation enables further speed improvement. In this article, we systematically study the effects of system truncations on binding affinity calculations obtained with FMO in combination with either the polarizable continuum model (FMO/PCM) or in combination with the Møller-Plesset method (FMO-MP2). We have used five protein complexes with ligands of several charged states. The calculated binding energies of the size variants of the truncated system, including only a restricted number of atoms around the ligand, are compared to the energy obtained from a full system. The result shows that the systems could be truncated to a radius of 8 Å from neutral ligands within an error of 0.7 kcal/mol, and 12 Å from charged ligands within an error of 1.1 kcal/mol for calculating the binding energy in solution.

QM/MM Well-Tempered Metadynamics Study of the Mechanism of XBP1 mRNA Cleavage by Inositol Requiring Enzyme 1α RNase

A range of in silico methodologies were herein employed to study the unconventional XBP1 mRNA cleavage mechanism performed by the unfolded protein response (UPR) mediator Inositol Requiring Enzyme 1α (IRE1). Using Protein-RNA molecular docking along with a series of extensive restrained/unrestrained atomistic molecular dynamics (MD) simulations, the dynamical behavior of the system was evaluated and a reliable model of the IRE1/XBP1 mRNA complex was constructed. From a series of well-converged quantum mechanics molecular mechanics well-tempered metadynamics (QM/MM WT-MetaD) simulations using the Grimme dispersion interaction corrected semiempirical parametrization method 6 level of theory (PM6-D3) and the AMBER14SB-OL3 force field, the free energy profile of the cleavage mechanism was determined, along with intermediates and transition state structures. The results show two distinct reaction paths based on general acid-general base type mechanisms, with different activation energies that perfectly match observations from experimental mutagenesis data. The study brings unique atomistic insights into the cleavage mechanism of XBP1 mRNA by IRE1 and clarifies the roles of the catalytic residues H910 and Y892. Increased understanding of the details in UPR signaling can assist in the development of new therapeutic agents for its modulation.

Ligand Strain and Its Conformational Complexity Is a Major Factor in the Binding of Cyclic Dinucleotides to STING Protein

STING (stimulator of interferon genes) is a key regulator of innate immunity that has recently been recognized as a promising drug target. STING is activated by cyclic dinucleotides (CDNs) which eventually leads to expression of type I interferons and other cytokines. Factors underlying the affinity of various CDN analogues are poorly understood. Herein, we correlate structural biology, isothermal calorimetry (ITC) and computational modeling to elucidate factors contributing to binding of six CDNs-three pairs of natural (ribo) and fluorinated (2'-fluororibo) 3',3'-CDNs. X-ray structural analyses of six {STING:CDN} complexes did not offer any explanation for the different affinities of the studied ligands. ITC showed entropy/enthalpy compensation up to 25 kcal mol-1 for this set of similar ligands. The higher affinities of fluorinated analogues are explained with help of computational methods by smaller loss of entropy upon binding and by smaller strain (free) energy.

SQM/COSMO Scoring Function: Reliable Quantum-Mechanical Tool for Sampling and Ranking in Structure-Based Drug Design

Quantum mechanical (QM) methods have been gaining importance in structure-based drug design where a reliable description of protein-ligand interactions is of utmost significance. However, strategies i. e. QM/MM, fragmentation or semiempirical (SQM) methods had to be pursued to overcome the unfavorable scaling of QM methods. Various SQM-based approaches have significantly contributed to the accuracy of docking and improvement of lead compounds. Parametrizations of SQM and implicit solvent methods in our laboratory have been instrumental to obtain a reliable SQM-based scoring function. The experience gained in its application for activity ranking of ligands binding to tens of protein targets resulted in setting up a faster SQM/COSMO scoring approach, which outperforms standard scoring methods in native pose identification for two dozen protein targets with ten thousand poses. Recently, SQM/COSMO was effectively applied in a proof-of-concept study of enrichment in virtual screening. Due to its superior performance, feasibility and chemical generality, we propose the SQM/COSMO approach as an efficient tool in structure-based drug design.

Near-Linear Scaling in DMRG-Based Tailored Coupled Clusters: An Implementation of DLPNO-TCCSD and DLPNO-TCCSD(T)

We present a new implementation of density matrix renormalization group based tailored coupled clusters method (TCCSD), which employs the domain-based local pair natural orbital approach (DLPNO). Compared to the previous local pair natural orbital (LPNO) version of the method, the new implementation is more accurate, offers more favorable scaling, and provides more consistent behavior across the variety of systems. On top of the singles and doubles, we include the perturbative triples correction (T), which is able to retrieve even more dynamic correlation. The methods were tested on three systems: tetramethyleneethane, oxo-Mn(Salen), and iron(II)-porphyrin model. The first two were revisited to assess the performance with respect to LPNO-TCCSD. For oxo-Mn(Salen), we retrieved between 99.8 and 99.9% of the total canonical correlation energy which is an improvement of 0.2% over the LPNO version in less than 63% of the total LPNO runtime. Similar results were obtained for iron(II)-porphyrin. When the perturbative triples correction was employed, irrespective of the active space size or system, the obtained energy differences between two spin states were within the chemical accuracy of 1 kcal/mol using the default DLPNO settings.

The interaction mechanism between alkaloids and pepsin based on lum-AuNPs in the chemiluminescence analysis

Herein, novel luminol functional gold nanoparticles (lum-AuNPs) were quickly prepared in an alkaline luminol solution with HAuCl₄, which had the unique characteristics of uniform size and excellent luminescence properties. A self-made flow injection-chemiluminescence (FI-CL) system was established to study the interaction between pepsin (Pep) and five alkaloids (anisodamine, berberine, reserpine, jatrorrhizine and matrine) using lum-AuNPs as the CL probe. Based on the abovementioned home-made CL system, the possible interaction mechanisms of Pep with five alkaloids have been comprehensively discussed by molecular docking simulation, chemical thermodynamics and kinetic studies. The results indicated that there were obvious CL enhancement and inhibition effects on the lum-AuNPs CL system for the Pep and the complex of Pep/alkaloids, respectively. The possible mechanism for the interaction of Pep–five alkaloids was mainly mediated by the hydrophobic force. The binding constant K and binding site n for the Pep–alkaloid interaction are consistent with the list of Ber > Res > Ani, Jat > Mat, which is relative to the potential of groups of alkaloids interacting with the active site of Pep.

A flow injection-chemiluminescence system was established to study the interaction between pepsin and five alkaloids, combined with lum-AuNPs.

Quantum Mechanics/Molecular Mechanics (QM/MM) Calculations Support a Concerted Reaction Mechanism for the Zika Virus NS2B/NS3 Serine Protease with Its Substrate

Zika virus (ZIKV) is mainly transmitted to humans by Aedes species mosquitoes and is associated with serious pathological disorders including microcephaly in newborns and Guillain-Barré syndrome in adults. Currently, there is no vaccine or anti-ZIKV drug available for preventing or controlling ZIKV infection. An attractive drug target for ZIKV treatment is a two-compartment (NS2B/NS3) serine protease that processes viral polyprotein during infection. Here, conventional molecular dynamics simulations of the ZIKV protease in complex with peptide substrate (TGKRS) sequence at the C-terminus of NS2B show that the substrate is in the active conformation for the cleavage reaction by ZIKV protease. Hybrid quantum mechanics/molecular mechanics (QM/MM) umbrella sampling simulations (PM6/ff14SB) of acylation results reveal that proton transfer from S135 to H51 and nucleophilic attack on the substrate by S135 are concerted. The rate-limiting step involves the formation of a tetrahedral intermediate. In addition, the single-point energy QM/MM calculations, precisely at the level of coupled cluster theory (LCCSD(T)/(aug)-cc-pVTZ), were performed to correct the potential energy profiles for the first step of the acylation process. The average computed activation barrier at this level of theory is 16.3 kcal mol^-1. Therefore, the computational approaches presented here are helpful for further designing of NS2B/NS3 inhibitors based on transition-state analogues.

Perturbative triples correction to domain-based local pair natural orbital variants of Mukherjee's state specific coupled cluster method

In this article we report an implementation of the perturbative triples correction to Mukherjee's state-specific multireference coupled cluster method based on the domain-based pair natural orbital approach (DLPNO-MkCC). We tested the performance of DLPNO-MkCCSD(T) in calculations involving tetramethyleneethane and isomers of naphthynes. These tests show that more than 97% of triples energy was recovered with respect to the canonical MkCCSD(T) method, which together with the DLPNO-MkCCSD part accounts for about 99.70-99.85% of the total correlation energy. The applicability of the method was demonstrated on calculations of singlet-triplet gaps for several large systems: triangulene, dynemicin A, and a beryllium complex.

Molecular Dynamics Simulation of Cyclooxygenase-2 Complexes with Indomethacin closo-Carborane Analogs

Molecular dynamics simulation of carborane-containing ligands in complex with target enzymes is a challenging task due to the unique structure and properties of the carborane substituents and relative lack of appropriate experimental data to help assess the quality of carborane force field parameters. Here, we report results from energy minimization calculations for a series of carborane-amino acid complexes using carborane force field parameters published previously in the literature and adapted for use with the AMBER ff99SB and ff14SB potential functions. These molecular mechanics results agree well with quantum mechanical geometry optimization calculations obtained using dispersion-corrected density functional theory methods, suggesting that the carborane force field parameters should be suitable for more detailed calculations. We then performed molecular dynamics simulations for the 1,2-, 1,7-, and 1,12-dicarba- closo-dodecaborane(12) derivatives of indomethacin methyl ester bound with cyclooxygenase-2. The simulation results suggest that only the ortho-carborane derivative forms a stable complex, in agreement with experimental findings, and provide insight into the possible molecular basis for isomer binding selectivity.

Use of the Multilayer Fragment Molecular Orbital Method to Predict the Rank Order of Protein-Ligand Binding Affinities: A Case Study Using Tankyrase 2 Inhibitors

In computational drug discovery, ranking a series of compound analogues in the order that is consistent with the experimental binding affinities remains a challenge. Many of the computational methods available for evaluating binding affinities have adopted molecular mechanics (MM)-based force fields, although they cannot completely describe protein-ligand interactions. By contrast, quantum mechanics (QM) calculations play an important role in understanding the protein-ligand interactions; however, their huge computational costs hinder their application in drug discovery. In this study, we have evaluated the ability to rank the binding affinities of tankyrase 2 ligands by combining both MM and QM calculations. Our computational approach uses the protein-ligand binding energies obtained from a cost-effective multilayer fragment molecular orbital (MFMO) method combined with the solvation energy obtained from the MM-Poisson-Boltzmann/surface area (MM-PB/SA) method to predict the binding affinity. This approach enabled us to rank tankyrase 2 inhibitor analogues, outperforming several MM-based methods, including rescoring by molecular docking and the MM-PB/SA method alone. Our results show that this computational approach using the MFMO method is a promising tool for predicting the rank order of the binding affinities of inhibitor analogues.

Assemble-And-Match: A Novel Hybrid Tool for Enhancing Education and Research in Rational Structure Based Drug Design

Rational drug design is the process of finding new medication that can activate or inhibit the biofunction of a target molecule by binding to it and forming a molecular complex. Here, shape and charge complementarities between drug and target are key. To help find effective drug molecules out of a huge pool of possibilities, physical and computer aided tools have been developed. Former offers a tangible experience of the molecular interactions yet lacks measurement and evaluation capabilities. Latter enables accurate and fast evaluations, but does not deliver the interactive tangible experience of physical models. We introduce a novel hybrid model called "Assemble-And-Match" where, we enhance and combine the unique features of the two categories. Assemble-And-Match works based on fabrication of customized molecular fragments using our developed software and a 3D printer. Fragments are hinged to each other in different combinations and form flexible peptide chains, conformable to tertiary structures, to fit in the binding pocket of a (3D printed) target molecule. Through embedded measurement marks, the molecular model is reconstructed in silico and its properties are evaluated. We expect Assemble-And-Match tool can enable combination of visuospatial perception with in silico computational power to aid research and education in drug design.

Computational biochemical investigation of the binding energy interactions between an estrogen receptor and its agonists

We present the energy profiles of estrogen receptor–agonist ligand interactions in atomic detail using a quantum biochemical approach.

Superior Performance of the SQM/COSMO Scoring Functions in Native Pose Recognition of Diverse Protein-Ligand Complexes in Cognate Docking

General and reliable description of structures and energetics in protein-ligand (PL) binding using the docking/scoring methodology has until now been elusive. We address this urgent deficiency of scoring functions (SFs) by the systematic development of corrected semiempirical quantum mechanical (SQM) methods, which correctly describe all types of noncovalent interactions and are fast enough to treat systems of thousands of atoms. Two most accurate SQM methods, PM6-D3H4X and SCC-DFTB3-D3H4X, are coupled with the conductor-like screening model (COSMO) implicit solvation model in so-called "SQM/COSMO" SFs and have shown unique recognition of native ligand poses in cognate docking in four challenging PL systems, including metalloprotein. Here, we apply the two SQM/COSMO SFs to 17 diverse PL complexes and compare their performance with four widely used classical SFs (Glide XP, AutoDock4, AutoDock Vina, and UCSF Dock). We observe superior performance of the SQM/COSMO SFs and identify challenging systems. This method, due to its generality, comparability across the chemical space, and lack of need for any system-specific parameters, gives promise of becoming, after comprehensive large-scale testing in the near future, a useful computational tool in structure-based drug design and serving as a reference method for the development of other SFs.

Noncovalent Interactions in Specific Recognition Motifs of Protein-DNA Complexes

In view of the importance of protein-DNA interactions in biological processes, we extracted from the Protein Data Bank several one-to-one complexes of amino acids with nucleotides that matched certain geometric and energetic specificity criteria and investigated them using quantum chemistry methods. The CCSD(T)/CBS interaction energies were used as a benchmark to compare the performance of the MP2.5, MP2-F12, DFT-D3, and PM6-D3H4 methods. All methods yielded good agreement with the reference values, with declining accuracy from MP2.5 to PM6-D3H4. Regardless of the site of interaction, the minima found after full optimization in implicit solvent with high dielectric constant were close to the structures experimentally detected in protein-DNA complexes. According to DFT-SAPT analysis, the nature of noncovalent interactions strongly depends on the type of amino acid. The negatively charged sugar-phosphate backbone of DNA heavily influences the strength of interactions and must be included in the computational model, especially in the case of interactions with charged amino acids.

Computational methods for the description of pharmacologically relevant platinum complexes--molecular structure and bond dissociation

Cancer is after cardiovascular disease the most frequent cause of death in Europe. In 28 of 53 countries considered in this area it is already the leading cause of death and expected to gain even more importance until the year 2020. Amongst the large arsenal of different anti-cancer drugs, platinum drugs belong to the first developed anticancer drugs and still have a large impact on cancer therapy. Nevertheless therapy with platinum-anticancer drugs is accompanied by severe adverse effects caused by frequent interactions with the amino acids of different human proteins. Computational chemistry offers methods to study such interactions and even those of not yet synthesized drugs in silico. For such studies a profound knowledge of the prediction quality of various computational methods towards platinum-drug-like complexes is necessary. By this article we are aiming on delivering important accuracy information of the frequently used computational methods. Most important findings are the high performance of the double hybrid functional B2PLYP for the calculation of geometries, even in small basis sets, followed by BP86 and PBE and the still acceptable performance of the semi-empirical Method PM6-D3H4X for extremely large systems. To follow absolute energies of the dissociation process, LPNO-CEPA and B3LYP-D3 can be suggested while SCS-MP2 shows an extremely narrow standard deviation and a low maximum error, which make it an ideal candidate for relative energy calculations in the exploration of reaction mechanisms.

Charge-dependent many-body exchange and dispersion interactions in combined QM/MM simulations

Accurate modeling of the molecular environment is critical in condensed phase simulations of chemical reactions. Conventional quantum mechanical/molecular mechanical (QM/MM) simulations traditionally model non-electrostatic non-bonded interactions through an empirical Lennard-Jones (LJ) potential which, in violation of intuitive chemical principles, is bereft of any explicit coupling to an atom's local electronic structure. This oversight results in a model whereby short-ranged exchange-repulsion and long-ranged dispersion interactions are invariant to changes in the local atomic charge, leading to accuracy limitations for chemical reactions where significant atomic charge transfer can occur along the reaction coordinate. The present work presents a variational, charge-dependent exchange-repulsion and dispersion model, referred to as the charge-dependent exchange and dispersion (QXD) model, for hybrid QM/MM simulations. Analytic expressions for the energy and gradients are provided, as well as a description of the integration of the model into existing QM/MM frameworks, allowing QXD to replace traditional LJ interactions in simulations of reactive condensed phase systems. After initial validation against QM data, the method is demonstrated by capturing the solvation free energies of a series of small, chlorine-containing compounds that have varying charge on the chlorine atom. The model is further tested on the SN2 attack of a chloride anion on methylchloride. Results suggest that the QXD model, unlike the traditional LJ model, is able to simultaneously obtain accurate solvation free energies for a range of compounds while at the same time closely reproducing the experimental reaction free energy barrier. The QXD interaction model allows explicit coupling of atomic charge with many-body exchange and dispersion interactions that are related to atomic size and provides a more accurate and robust representation of non-electrostatic non-bonded QM/MM interactions.

Recent Progress in Treating Protein-Ligand Interactions with Quantum-Mechanical Methods

We review the first successes and failures of a “new wave” of quantum chemistry-based approaches to the treatment of protein/ligand interactions. These approaches share the use of “enhanced”, dispersion (D), and/or hydrogen-bond (H) corrected density functional theory (DFT) or semi-empirical quantum mechanical (SQM) methods, in combination with ensemble weighting techniques of some form to capture entropic effects. Benchmark and model system calculations in comparison to high-level theoretical as well as experimental references have shown that both DFT-D (dispersion-corrected density functional theory) and SQM-DH (dispersion and hydrogen bond-corrected semi-empirical quantum mechanical) perform much more accurately than older DFT and SQM approaches and also standard docking methods. In addition, DFT-D might soon become and SQM-DH already is fast enough to compute a large number of binding modes of comparably large protein/ligand complexes, thus allowing for a more accurate assessment of entropic effects.

The SQM/COSMO filter: reliable native pose identification based on the quantum-mechanical description of protein–ligand interactions and implicit COSMO solvation

Strictly uphill – in cognate docking experiments we show that a quantum mechanical description of interaction and solvation outperforms established scoring functions in sharply distinguishing the native state from decoy poses.

Binding affinities by alchemical perturbation using QM/MM with a large QM system and polarizable MM model

The most general way to improve the accuracy of binding-affinity calculations for protein-ligand systems is to use quantum-mechanical (QM) methods together with rigorous alchemical-perturbation (AP) methods. We explore this approach by calculating the relative binding free energy of two synthetic disaccharides binding to galectin-3 at a reasonably high QM level (dispersion-corrected density functional theory with a triple-zeta basis set) and with a sufficiently large QM system to include all short-range interactions with the ligand (744-748 atoms). The rest of the protein is treated as a collection of atomic multipoles (up to quadrupoles) and polarizabilities. Several methods for evaluating the binding free energy from the 3600 QM calculations are investigated in terms of stability and accuracy. In particular, methods using QM calculations only at the endpoints of the transformation are compared with the recently proposed non-Boltzmann Bennett acceptance ratio (NBB) method that uses QM calculations at several stages of the transformation. Unfortunately, none of the rigorous approaches give sufficient statistical precision. However, a novel approximate method, involving the direct use of QM energies in the Bennett acceptance ratio method, gives similar results as NBB but with better precision, ∼3 kJ/mol. The statistical error can be further reduced by performing a greater number of QM calculations.

Benchmark of electronic structure methods for protein–ligand interactions based on high-level reference data

The accurate prediction of the strength of protein–ligand interactions is a very difficult problem despite impressive advances in the field of biomolecular modeling. There are good reasons to believe that quantum mechanical methods can help with this task, but the application of such methods in the context of scoring is still in its infancy. Here we benchmark several wave function theory (WFT), density functional theory (DFT) and semiempirical quantum mechanical (SQM) approaches against high-level theoretical references for realistic test cases. Based on our findings for systematically generated model systems of real protein/ligand complexes from the PDB-bind database, we can recommend SCS-MP2 and B2-PLYP-D3 as reference methods, TPSS-D3+Dabc/def-TZVPP as the best DFT approach and PM6-DH+ as a fast and accurate alternative to full ab initio treatments.

Quantum molecular modelling of ibuprofen bound to human serum albumin

The total interaction energies of the ibuprofen complexed with FA3/FA4 and FA6 binding sites of human serum albumin are in agreement with the hypothesis that the Sudlow's site II is the main binding pocket for ibuprofen.

Current and emerging opportunities for molecular simulations in structure-based drug design

An overview of the current capabilities and limitations of molecular simulation of biomolecular complexes in the context of computer-aided drug design is provided. Steady improvements in computer hardware coupled with more refined representations of energetics are leading to a new appreciation of the driving forces of molecular recognition. Molecular simulations are poised to more frequently guide the interpretation of biophysical measurements of biomolecular complexes. Ligand design strategies emerge from detailed analyses of computed structural ensembles. The feasibility of routine applications to ligand optimization problems hinges upon successful extensive large scale validation studies and the development of protocols to intelligently automate computations.

Potency prediction of β-secretase (BACE-1) inhibitors using density functional methods

Scoring potency is a main challenge for structure based drug design. Inductive effects of subtle variations in the ligand are not possible to accurately predict by classical computational chemistry methods. In this study, the problem of predicting potency of ligands with electronic variations participating in key interactions with the protein was addressed. The potency was predicted for a large set of cyclic amidine and guanidine cores extracted from β-secretase (BACE-1) inhibitors. All cores were of similar size and had equal interaction motifs but were diverse with respect to electronic substitutions. A density functional theory approach, in combination with a representation of the active site of a protein using only key residues, was shown to be predictive. This computational approach was used to guide and support drug design, within the time frame of a normal drug discovery design cycle.

Chemical applications carried out by local pair natural orbital based coupled-cluster methods

Local pair natural orbital coupled-cluster methods are suitable for accurate assessment of the energies of large molecular and supramolecular systems.