A new method for estimating the importance of hydrogen-bonding groups in the binding site of a protein

We introduce a new method to estimate the importance of hydrogen-bonding sitepoints in the binding site of a protein as part of a structure-based design strategy. Our method identifies hydrogen-bonding sitepoints within a binding pocket and ranks them according to both the accessibility of their hydrogen bonding regions to incoming ligands and their hydrogen-bonding strength. The combination of these components produces a prioritised list of sitepoints that are more likely to be involved in hydrogen bonding with an incoming ligand. A dataset of known protein-ligand interactions was used to compare the prioritisation of sitepoints identified by our method with those observed to be engaged in hydrogen bonding in their crystal structures. Our method was able to remove those sitepoints unable to bind the ligand due to a low accessibility or an unfavourable orientation and to award significantly higher hydrogen-bonding ranking values to those sitepoints observed to form hydrogen bonds. Our method can thus be used to identify hydrogen-bonding sitepoints that should be targeted preferentially in a drug design strategy.     

ENPDA: an evolutionary structure-based <Emphasis Type="Italic">de novo</Emphasis> peptide design algorithm

Summary One of the goals of computational chemists is to automate the de novo design of bioactive molecules. Despite significant advances in computational approaches to ligand design and binding energy evaluation, novel procedures for ligand design are required. Evolutionary computation provides a new approach to this design endeavor. We propose an evolutionary tool for de novo peptide design, based on the evaluation of energies for peptide binding to a user-defined protein surface patch. Special emphasis has been placed on the evaluation of the proposed peptides, leading to two different evaluation heuristics. The software developed was successfully tested on the design of ligands for the proteins prolyl oligopeptidase, p53, and DNA gyrase.     

Computational chemistry in drug lead discovery and design

The main contributions of our group during the last 15 years developing and using biomolecular simulation tools in drug lead discovery and design, in close collaboration with experimental researchers, are presented. Special emphasis has been given to methodological improvements in the following areas: (1) target homology modeling incorporating knowledge about known ligands to accurately characterize the binding site; (2) designing alternative strategies to account for protein flexibility in high-throughput docking; (3) development of stochastic- and normal-mode-based methods to de novo design structurally diverse protein conformers; (4) development and validation of quantum mechanical semi-empirical linear-scaling calculations to correctly estimate ligand binding free energy. Several successful cases of computer-aided drug discovery are also presented, especially our recent work on viral targets.     

Classification of water molecules in protein binding sites

Water molecules play a crucial role in mediating the interaction between a ligand and a macromolecular receptor. An understanding of the nature and role of each water molecule in the active site of a protein could greatly increase the efficiency of rational drug design approaches: if the propensity of a water molecule for displacement can be determined, then synthetic effort may be most profitably applied to the design of specific ligands with the displacement of this water molecule in mind. In this paper, a thermodynamic analysis of water molecules in the binding sites of six proteins, each complexed with a number of inhibitors, is presented. Two classes of water molecules were identified: those conserved and not displaced by any of the ligands, and those that are displaced by some ligands. The absolute binding free energies of 54 water molecules were calculated using the double decoupling method, with replica exchange thermodynamic integration in Monte Carlo simulations. It was found that conserved water molecules are on average more tightly bound than displaced water molecules. In addition, Bayesian statistics is used to calculate the probability that a particular water molecule may be displaced by an appropriately designed ligand, given the calculated binding free energy of the water molecule. This approach therefore allows the numerical assessment of whether or not a given water molecule should be targeted for displacement as part of a rational drug design strategy.     

Including tightly-bound water molecules in de novo drug design. Exemplification through the in silico generation of poly(ADP-ribose)polymerase ligands

Different strategies for the in silico generation of ligand molecules in the binding site of poly(ADP-ribose)polymerase (PARP) were studied in order to observe the effect of the targeting and displacement of tightly bound water molecules. Several molecular scaffolds were identified as having better interactions in the binding site when targeting one or two tightly bound water molecules in the NAD binding site. Energy calculations were conducted in order to assess the ligand-protein and ligand-water-protein interactions of different functional groups of the generated ligands. These calculations were used to evaluate the energetic consequences of the presence of tightly bound water molecules and to identify those that contribute favorably to the binding of ligands.     

What Can We Learn from Molecular Recognition in Protein–Ligand Complexes for the Design of New Drugs?

The understanding of noncovalent interactions in protein–ligand complexes is essential in modern biochemistry and should contribute toward the discovery of new drugs. In the present review, we summarize recent work aimed at a better understanding of the physical nature of molecular recognition in protein–ligand complexes and also at the development and application of new computational tools that exploit our current knowledge on structural and energetic aspects of protein–ligand interactions in the design of novel ligands. These approaches are based on the exponentially growing amount of information about the geometry of protein structures and the properties of small organic molecules exposed to a structured molecular environment. The various contributions that determine the binding affinity of ligands toward a particular receptor are discussed. Their putative binding site conformations are analyzed, and some predictions are attempted. The similarity of ligands is examined with respect to their recognition properties. This information is used to understand and propose binding modes. In addition, an overview of the existing methods for the design and selection of novel protein ligands is given.     

Hydration in drug design. 2. Influence of local site surface shape on water binding

Summary If water molecules are strongly bound at a protein-ligand interface, they are unlikely to be displaced during ligand binding. Such water molecules can change the shape of the ligand binding site and thus affect strategies for drug design. To understand the nature of water binding, and factors influencing it, water molecules at the ligand binding sites of 26 high-resolution protein-ligand complexes have been examined here. Water molecules bound in deep grooves and cavities between the protein and the ligand are located in the indentations on the protein-site surface, but not in the indentations on the ligand surface. The majority of the water molecules bound in deep indentations on the protein-site surface make multiple polar contacts with the protein surface. This may indicate a strong binding of water molecules in deep indentations on protein-site surfaces. The local shape of the site surface may influence the binding of water molecules that mediate protein-ligand interactions.     

Hydration in drug design. 1. Multiple hydrogen-bonding features of water molecules in mediating protein-ligand interactions

Summary Water is known to play an important rôle in the recognition and stabilization of the interaction between a ligand and its site. This has important implications for drug design. Analyses of 19 high-resolution crystal structures of protein-ligand complexes reveal the multiple hydrogen-bonding feature of water molecules mediating protein-ligand interactions. Most of the water molecules (nearly 80%) involved in bridging the protein and the ligand can make three or more hydrogen bonds when distance and bond angles are used as criteria to define hydrogen-bonding interactions. Isotropic B-factors have been used to take into account the mobility of water molecules. The water molecules at binding sites bridge the protein and ligand, and interact with other water molecules to form a complex network of interconnecting hydrogen bonds. Some water molecules at the site do not directly bridge between the protein and the ligand, but may contribute indirectly to the stability of the complex by holding bridging water molecules in the right position through a network of hydrogen bonds. These water networks are probably crucial for the stability of the protein-ligand complex and are important for any site-directed drug design strategies.     

De novo design based identification of potential HIV-1 integrase inhibitors: A pharmacoinformatics study

In the present study, pharmacoinformatics paradigms include receptor-based de novo design, virtual screening through molecular docking and molecular dynamics (MD) simulation are implemented to identify novel and promising HIV-1 integrase inhibitors. The de novodrug/ligand/molecule design is a powerful and effective approach to design a large number of novel and structurally diverse compounds with the required pharmacological profiles. A crystal structure of HIV-1 integrase bound with standard inhibitor BI-224436 is used and a set of 80,000 compounds through the de novo approach in LigBuilder is designed. Initially, a number of criteria including molecular docking, in-silico toxicity and pharmacokinetics profile assessments are implied to reduce the chemical space. Finally, four de novo designed molecules are proposed as potential HIV-1 integrase inhibitors based on comparative analyses. Notably, strong binding interactions have been identified between a few newly identified catalytic amino acid residues and proposed HIV-1 integrase inhibitors. For evaluation of the dynamic stability of the protein-ligand complexes, a number of parameters are explored from the 100 ns MD simulation study. The MD simulation study suggested that proposed molecules efficiently retained their molecular interaction and structural integrity inside the HIV-1 integrase. The binding free energy is calculated through the Molecular Mechanics Poisson-Boltzmann Surface Area (MM-PBSA) approach for all complexes and it also explains their thermodynamic stability. Hence, proposed molecules through de novo design might be critical to inhibiting the HIV-1 integrase.     

Molecular modelling prediction of ligand binding site flexibility

We have investigated the efficacy of generating multiple sidechain conformations using a rotamer library in order to find the experimentally observed ligand binding site conformation of a protein in the presence of a bound ligand. We made use of a recently published algorithm that performs an exhaustive conformational search using a rotamer library to enumerate all possible sidechain conformations in a binding site. This approach was applied to a dataset of proteins whose structures were determined by X-ray and NMR methods. All chosen proteins had two or more structures, generally involving different bound ligands. By taking one of these structures as a reference, we were able in most cases to successfully reproduce the experimentally determined conformations of the other structures, as well as to suggest alternative low-energy conformations of the binding site. In those few cases where this procedure failed, we observed that the bound ligand had induced a high-energy conformation of the binding site. These results suggest that for most proteins that exhibit limited backbone motion, ligands tend to bind to low energy conformations of their binding sites. Our results also reveal that it is possible in most cases to use a rotamer search-based approach to predict alternative low-energy protein binding site conformations that can be used by different ligands. This opens the possibility of incorporating alternative binding site conformations to improve the efficacy of docking and structure-based drug design algorithms.     

Hydration in drug design. 3. Conserved water molecules at the ligand-binding sites of homologous proteins

Summary Water molecules are known to play an important rôle in mediating protein-ligand interactions. If water molecules are conserved at the ligand-binding sites of homologous proteins, such a finding may suggest the structural importance of water molecules in ligand binding. Structurally conserved water molecules change the conventional definition of binding sites by changing the shape and complementarity of these sites. Such conserved water molecules can be important for site-directed ligand/drug design. Therefore, five different sets of homologous protein/protein-ligand complexes have been examined to identify the conserved water molecules at the ligand-binding sites. Our analysis reveals that there are as many as 16 conserved water molecules at the FAD binding site of glutathione reductase between the crystal structures obtained from human and E. coli. In the remaining four sets of high-resolution crystal structures, 2–4 water molecules have been found to be conserved at the ligand-binding sites. The majority of these conserved water molecules are either bound in deep grooves at the protein-ligand interface or completely buried in cavities between the protein and the ligand. All these water molecules, conserved between the protein/protein-ligand complexes from different species, have identical or similar apolar and polar interactions in a given set. The site residues interacting with the conserved water molecules at the ligand-binding sites have been found to be highly conserved among proteins from different species; they are more conserved compared to the other site residues interacting with the ligand. These water molecules, in general, make multiple polar contacts with protein-site residues.     

CONCEPTS: New dynamic algorithm for de novo drug suggestion

We describe a new method for de novo design of molecules that bind to protein active sites. The method, CONCEPTS (Creation of Novel Compounds by Evaluation of Particles at Target Sites), places a group of atom-like particles in the site. The particles are free to move within the site to improve binding to the protein. A key innovation of this technique is that covalent connections are made among the particles in a stochastic and dynamically reversible manner. These changes in the topology are either accepted or rejected depending on their ability to improve the total energy of the enzyme–inhibitor complex. The method is applied to two test systems: The FK506 binding protein (FKBP-12) and HIV-1 aspartyl protease. In both cases, we are able to predict, de novo, drugs that have striking similarities to known potent inhibitors and that can successfully be used to generate “hits” of the known inhibitors from a data base. © John Wiley & Sons, Inc.     

Ligand-protein docking with water molecules

The presence of water molecules plays an important role in the accuracy of ligand-protein docking predictions. Comprehensive docking simulations have been performed on a large set of ligand-protein complexes whose crystal structures contain water molecules in their binding sites. Only those water molecules found in the immediate vicinity of both the ligand and the protein were considered. We have investigated whether prior optimization of the orientation of water molecules in either the presence or absence of the bound ligand has any effect on the accuracy of docking predictions. We have observed a statistically significant overall increase in accuracy when water molecules are included during docking simulations and have found this to be independent of the method of optimization of the orientation of water molecules. These results confirm the importance of including water molecules whenever possible in a ligand-protein docking simulation. Our findings also reveal that prior optimization of the orientation of water molecules, in the absence of any bound ligand, does not have a detrimental effect on the improved accuracy of ligand-protein docking. This is important, given the use of docking simulations to predict the binding modes of new ligands or drug molecules.     

Development and testing of a de novo drug-design algorithm

In this article we present an implementation of a de novo drug-design algorithm. The algorithm starts with a molecule placed in the binding site of a protein and then modifies it using a sequential growth approach. This involves successive cycles of suppression of randomly picked groups in the molecule and their replacement by other groups chosen from databanks of linear or cyclic fragments. The algorithm has been coupled with the Dynamo library which allows the simulation of macromolecules using molecular mechanical and quantum chemical methods. The main body of the article describes the methodologies we use to create, characterize and evaluate putative ligands. We also consider briefly an application of the algorithm to a protein of pharmacological interest, the neuraminidase of the influenza virus, and discuss the strengths and weaknesses of our approach.     

A validation study on the practical use of automated de novo design

The de novo design program Skelgen has been used to design inhibitor structures for four targets of pharmaceutical interest. The designed structures are compared to modeled binding modes of known inhibitors (i) visually and (ii) by means of a novel similarity measure considering the size and spatial proximity of the maximum common substructure of two small molecules. It is shown that the Skelgen algorithm generates representatives of many inhibitor classes within a very short time and that the new similarity measure is useful for comparing and clustering designed structures. The results demonstrate the necessity of properly defining search constraints in practical applications of de novo design.     

Genetic algorithm for the design of molecules with desired properties

The design of molecules with desired properties is still a challenge because of the largely unpredictable end results. Computational methods can be used to assist and speed up this process. In particular, genetic algorithms have proved to be powerful tools with a wide range of applications, e.g. in the field of drug development. Here, we propose a new genetic algorithm that has been tailored to meet the demands of de novo drug design, i.e. efficient optimization based on small training sets that are analyzed in only a small number of design cycles. The efficiency of the design algorithm was demonstrated in the context of several different applications. First, RNA molecules were optimized with respect to folding energy. Second, a spinglass was optimized as a model system for the optimization of multiletter alphabet biopolymers such as peptides. Finally, the feasibility of the computer-assisted molecular design approach was demonstrated for the de novo construction of peptidic thrombin inhibitors using an iterative process of 4 design cycles of computer-guided optimization. Synthesis and experimental fitness determination of only 600 different compounds from a virtual library of more than 10¹⁷ molecules was necessary to achieve this goal.These authors contributed equally to the results presentedThese authors contributed equally to the results presentedThese authors contributed equally to the results presentedThese authors contributed equally to the results presented     

Water molecules inside protein structure affect binding of monosaccharides with HIV‐1 antibody 2G12

Water molecules inside biomolecules constitute integral parts of their structure and participate in the functions of the proteins. Some of the X‐ray crystallographic data are insufficient for analyzing a series of ligand–protein complexes in the same condition. We theoretically investigated antibody binding abilities of saccharide ligands and the effects of the inner water molecules of ligand–antibody complexes. Classical molecular dynamics and quantum chemical simulations using a model with possible water molecules inside the protein were performed with saccharide ligands and Human Immunodeficiency Virus 1 neutralizing antibody 2G12 complexes to estimate how inner water molecules of the protein affect the dynamics of the complexes as well as the ligand–antibody interaction. Our results indicate the fact that d ‐fructose's strong affinity to the antibody was partly due to the good retentiveness of solvent water molecules of the ligand and its stability of the ligand's conformation and relative position in the active site. © 2016 Wiley Periodicals, Inc.     

Accurate predictions of nonpolar solvation free energies require explicit consideration of binding-site hydration

Continuum solvation methods are frequently used to increase the efficiency of computational methods to estimate free energies. In this paper, we have evaluated how well such methods estimate the nonpolar solvation free-energy change when a ligand binds to a protein. Three different continuum methods at various levels of approximation were considered, viz., the polarized continuum model (PCM), a method based on cavity and dispersion terms (CD), and a method based on a linear relation to the solvent-accessible surface area (SASA). Formally rigorous double-decoupling thermodynamic integration was used as a benchmark for the continuum methods. We have studied four protein-ligand complexes with binding sites of varying solvent exposure, namely the binding of phenol to ferritin, a biotin analogue to avidin, 2-aminobenzimidazole to trypsin, and a substituted galactoside to galectin-3. For ferritin and avidin, which have relatively hidden binding sites, rather accurate nonpolar solvation free energies could be obtained with the continuum methods if the binding site is prohibited to be filled by continuum water in the unbound state, even though the simulations and experiments show that the ligand replaces several water molecules upon binding. For the more solvent exposed binding sites of trypsin and galectin-3, no accurate continuum estimates could be obtained, even if the binding site was allowed or prohibited to be filled by continuum water. This shows that continuum methods fail to give accurate free energies on a wide range of systems with varying solvent exposure because they lack a microscopic picture of binding-site hydration as well as information about the entropy of water molecules that are in the binding site before the ligand binds. Consequently, binding affinity estimates based upon continuum solvation methods will give absolute binding energies that may differ by up to 200 kJ/mol depending on the method used. Moreover, even relative energies between ligands with the same scaffold may differ by up to 75 kJ/mol. We have tried to improve the continuum solvation methods by adding information about the solvent exposure of the binding site or the hydration of the binding site, and the results are promising at least for this small set of complexes.     

Stalis: A Computational Method for Template-Based Ab Initio Ligand Design

Proteins interact with small molecules through specific molecular recognition, which is central to essential biological functions in living systems. Therefore, understanding such interactions is crucial for basic sciences and drug discovery. Here, we present S tructure t emplate-based a b initio li gand design s olution (Stalis), a knowledge-based approach that uses structure templates from the Protein Data Bank libraries of whole ligands and their fragments and generates a set of molecules (virtual ligands) whose structures represent the pocket shape and chemical features of a given target binding site. Our benchmark performance evaluation shows that ligand structure-based virtual screening using virtual ligands from Stalis outperforms a receptor structure-based virtual screening using AutoDock Vina, demonstrating reliable overall screening performance applicable to computational high-throughput screening. However, virtual ligands from Stalis are worse in recognizing active compounds at the small fraction of a rank-ordered list of screened library compounds than crystal ligands, due to the low resolution of the virtual ligand structures. In conclusion, Stalis can facilitate drug discovery research by designing virtual ligands that can be used for fast ligand structure-based virtual screening. Moreover, Stalis provides actual three-dimensional ligand structures that likely bind to a target protein, enabling to gain structural insight into potential ligands. Stalis can be an efficient computational platform for high-throughput ligand design for fundamental biological study and drug discovery research at the proteomic level. © 2019 Wiley Periodicals, Inc.     

Mechanism of OMP decarboxylation in orotidine 5'-monophosphate decarboxylase

Despite extensive experimental and theoretical studies, the detailed catalytic mechanism of orotidine 5'-monophosphate decarboxylase (ODCase) remains controversial. In particular simulation studies using high level quantum mechanics have failed to reproduce experimental activation free energy. One common feature of many previous simulations is that there is a water molecule in the vicinity of the leaving CO2 group whose presence was only observed in the inhibitor bound complex of ODCase/BMP. Various roles have even been proposed for this water molecule from the perspective of stabilizing the transition state and/or intermediate state. We hypothesize that this water molecule is not present in the active ODCase/OMP complex. Based on QM/MM minimum free energy path simulations with accurate density functional methods, we show here that in the absence of this water molecule the enzyme functions through a simple direct decarboxylation mechanism. Analysis of the interactions in the active site indicates multiple factors contributing to the catalysis, including the fine-tuned electrostatic environment of the active site and multiple hydrogen-bonding interactions. To understand better the interactions between the enzyme and the inhibitor BMP molecule, simulations were also carried out to determine the binding free energy of this special water molecule in the ODCase/BMP complex. The results indicate that the water molecule in the active site plays a significant role in the binding of BMP by contributing approximately -3 kcal/mol to the binding free energy of the complex. Therefore, the complex of BMP plus a water molecule, instead of the BMP molecule alone, better represents the tight binding transition state analogue of ODCase. Our simulation results support the direct decarboxylation mechanism and highlight the importance of proper recognition of protein bound water molecules in the protein-ligand binding and the enzyme catalysis.