Antibody mutations favoring pH-dependent binding in solid tumor microenvironments: Insights from large-scale structure-based calculations.

Antibody-based therapeutics for treatment of various tumors have grown rapidly in recent years. Unfortunately, safety issues, attributed to off-tumor effects and cytotoxicity, are still a significant concern with the standard of care. Improvements to ensure targeted delivery of antitumor pharmaceuticals are desperately needed. We previously demonstrated that incorporating histidyl pH-switches in an anti-HER2 antibody induced selective antigen binding under acidic pH conditions (MAbs 2020;12:1682866). This led to an improved safety profile due to preferential targeting of the oncoprotein in the acidic solid tumor microenvironment. Following this success, we expanded this approach to a set of over 400 antibody structures complexed with over 100 different human oncoproteins, associated with solid tumors. Calculations suggested that mutations to His of certain residue types, namely Trp, Arg, and Tyr, could be significantly more successful for inducing pH-dependent binding under acidic conditions. Furthermore, 10 positions within the complementarity-determining region were also predicted to exhibit greater successes. Combined, these two accessible metrics could serve as the basis for a sequence-based engineering of pH-selective binding. This approach could be applied to most anticancer antibodies, which lack detailed structural characterization.

Binding pose and affinity prediction in the 2016 D3R Grand Challenge 2 using the Wilma-SIE method.

The Farnesoid X receptor (FXR) exhibits significant backbone movement in response to the binding of various ligands and can be a challenge for pose prediction algorithms. As part of the D3R Grand Challenge 2, we tested Wilma-SIE, a rigid-protein docking method, on a set of 36 FXR ligands for which the crystal structures had originally been blinded. These ligands covered several classes of compounds. To overcome the rigid protein limitations of the method, we used an ensemble of publicly available structures for FXR from the PDB. The use of the ensemble allowed Wilma-SIE to predict poses with average and median RMSDs of 2.3 and 1.4 Å, respectively. It was quite clear, however, that had we used a single structure for the receptor the success rate would have been much lower. The most successful predictions were obtained on chemical classes for which one or more crystal structures of the receptor bound to a molecule of the same class was available. In the absence of a crystal structure for the class, observing a consensus binding mode for the ligands of the class using one or more receptor structures of other classes seemed to be indicative of a reasonable pose prediction. Affinity prediction proved to be more challenging with generally poor correlation with experimental IC50s (Kendall tau ~ 0.3). Even when the 36 crystal structures were used the accuracy of the predicted affinities was not appreciably improved. A possible cause of difficulty is the internal energy strain arising from conformational differences in the receptor across complexes, which may need to be properly estimated and incorporated into the SIE scoring function.

Structural Studies of Trypanosoma brucei RNA Editing Ligases and Their Binding Partner Proteins.

To study the mechanism of ligating nicked RNA strands, we conducted molecular dynamics simulations of Trypanosoma brucei RNA editing ligases L1 and L2 complexed with double-stranded RNA (dsRNA) fragments. In each resulting model, a Mg(2+) ion coordinates the 5'-PO4 of the nicked nucleotide and the 3'-OH of the terminal nucleotide for a nucleophilic reaction consistent with the postulated step 3 chemistry of the ligation mechanism. Moreover, coordination of the 3'-OH to the Mg(2+) ion may lower its pKa, thereby rendering it a more effective nucleophile as an oxyanion. Thus, Mg(2+) may play a twofold role: bringing the reactants into the proximity of each other and activating the nucleophile. We also conducted solvated interaction energy calculations to explore whether ligation specificities can be correlated to ligase-dsRNA binding affinity changes. The calculated dsRNA binding affinities are stronger for both L1 and L2 when the terminal nucleotide is changed from cytosine to guanine, in line with their experimentally measured ligation specificities. Because the ligation mechanism is also influenced by interactions of the ligase with partner proteins from the editosome subcomplex, we also modeled the structure of the RNA-bound L2 in complex with the oligonucleotide binding (OB) domain of largest editosome interacting protein A1. The resulting L2-dsRNA-A1 model, which is consistent with mutagenesis and binding data recorded to date, provides the first atomic-level glimpse of plausible interactions around the RNA ligation site in the presence of an OB domain presented in-trans to a nucleic acid ligase.

Evaluation of the Wilma-SIE Virtual Screening Method in Community Structure-Activity Resource 2013 and 2014 Blind Challenges.

Prospective assessments of the Wilma-SIE (solvated interaction energy) platform for ligand docking and ranking were performed during the 2013 and 2014 editions of the Community Structure-Activity Resource (CSAR) blind challenge. Diverse targets like a steroid-binding protein, a serine protease (factor Xa), a tyrosine kinase (Syk), and a nucleotide methyltransferase (TrmD) were included. Pose selection was achieved with high precision; in all 24 tests Wilma-SIE top-ranked the native pose among carefully generated sets of decoy conformations. Good separation for the native pose was also observed indicating robustness in pose scoring. Cross-docking was also accomplished with high accuracy for the various systems, with ligand median-RMSD values around 1 Å from the crystal structures. Larger deviations were occasionally obtained due to the rigid-target approach even if multiple target structures were used. Affinity ranking of congeneric ligands after cross-docking was reasonable for three of the four systems, with Spearman ranking coefficients around 0.6. Poor affinity ranking for FXa is possibly due to missing structural domains, which are present during measurements. Assignment of protonation states is critical for affinity scoring with the SIE function, as shown here for the Syk system. Including the FiSH model improved cross-docking but worsened affinity predictions, pointing to the need for further fine-tuning of this newer solvation model. The consistently strong performance of the Wilma-SIE platform in recent CSAR and SAMPL blind challenges validates its applicability for virtual screening on a broad range of molecular targets.

Assessment of Solvated Interaction Energy Function for Ranking Antibody-Antigen Binding Affinities.

Affinity modulation of antibodies and antibody fragments of therapeutic value is often required in order to improve their clinical efficacies. Virtual affinity maturation has the potential to quickly focus on the critical hotspot residues without the combinatorial explosion problem of conventional display and library approaches. However, this requires a binding affinity scoring function that is capable of ranking single-point mutations of a starting antibody. We focus here on assessing the solvated interaction energy (SIE) function that was originally developed for and is widely applied to scoring of protein-ligand binding affinities. To this end, we assembled a structure-function data set called Single-Point Mutant Antibody Binding (SiPMAB) comprising several antibody-antigen systems suitable for this assessment, i.e., based on high-resolution crystal structures for the parent antibodies and coupled with high-quality binding affinity measurements for sets of single-point antibody mutants in each system. Using this data set, we tested the SIE function with several mutation protocols based on the popular methods SCWRL, Rosetta, and FoldX. We found that the SIE function coupled with a protocol limited to sampling only the mutated side chain can reasonably predict relative binding affinities with a Spearman rank-order correlation coefficient of about 0.6, outperforming more aggressive sampling protocols. Importantly, this performance is maintained for each of the seven system-specific component subsets as well as for other relevant subsets including non-alanine and charge-altering mutations. The transferability and enrichment in affinity-improving mutants can be further enhanced using consensus ranking over multiple methods, including the SIE, Talaris, and FOLDEF energy functions. The knowledge gained from this study can lead to successful prospective applications of virtual affinity maturation.

Transcription factor substitution during the evolution of fungal ribosome regulation.

Coordinated ribosomal protein (RP) gene expression is crucial for cellular viability, but the transcriptional network controlling this regulon has only been well characterized in the yeast Saccharomyces cerevisiae. We have used whole-genome transcriptional and location profiling to establish that, in Candida albicans, the RP regulon is controlled by the Myb domain protein Tbf1 working in conjunction with Cbf1. These two factors bind both the promoters of RP genes and the rDNA locus; Tbf1 activates transcription at these loci and is essential. Orthologs of Tbf1 bind TTAGGG telomeric repeats in most eukaryotes, and TTAGGG cis-elements are present upstream of RP genes in plants and fungi, suggesting that Tbf1 was involved in both functions in ancestral eukaryotes. In all Hemiascomycetes, Rap1 substituted Tbf1 at telomeres and, in the S. cerevisiae lineage, this substitution also occurred independently at RP genes, illustrating the extreme adaptability and flexibility of transcriptional regulatory networks.

Allosteric noncompetitive small molecule selective inhibitors of CD45 tyrosine phosphatase suppress T-cell receptor signals and inflammation in vivo.

CD45 is a receptor-like member of the protein tyrosine phosphatase (PTP) family. We screened in silico for small molecules binding at a predicted allosteric pocket unique to the CD45 intracellular domain, and validated inhibitors by in vitro phosphatase assays. Compound 211 exhibited a CD45 IC50 value of 200 nM and had >100-fold selectivity over six related PTPs. The relevance of the allosteric pocket was verified through site-directed mutagenesis. Compound 211 has a noncompetitive mechanism of action, and it is extremely effective at preventing dephosphorylation of substrate Lck phosphotyrosine (pY)-505 versus preventing dephosphorylation of Lck pY-393. In cultured primary T cells, compound 211 prevents T-cell receptor-mediated activation of Lck, Zap-70, and mitogen-activated protein kinase, and interleukin-2 production. In a delayed-type hypersensitivity reaction in vivo, compound 211 abolished inflammation. This work demonstrates a novel approach to develop effective allosteric inhibitors that can be expanded to target the corresponding allosteric domains of other receptor PTPs.

Small-molecule inhibitors of the pseudaminic acid biosynthetic pathway: targeting motility as a key bacterial virulence factor.

Helicobacter pylori is motile by means of polar flagella, and this motility has been shown to play a critical role in pathogenicity. The major structural flagellin proteins have been shown to be glycosylated with the nonulosonate sugar, pseudaminic acid (Pse). This glycan is unique to microorganisms, and the process of flagellin glycosylation is required for H. pylori flagellar assembly and consequent motility. As such, the Pse biosynthetic pathway offers considerable potential as an antivirulence drug target, especially since motility is required for H. pylori colonization and persistence in the host. This report describes screening the five Pse biosynthetic enzymes for small-molecule inhibitors using both high-throughput screening (HTS) and in silico (virtual screening [VS]) approaches. Using a 100,000-compound library, 1,773 hits that exhibited a 40% threshold inhibition at a 10 µM concentration were identified by HTS. In addition, VS efforts using a 1.6-million compound library directed at two pathway enzymes identified 80 hits, 4 of which exhibited reasonable inhibition at a 10 µM concentration in vitro. Further secondary screening which identified 320 unique molecular structures or validated hits was performed. Following kinetic studies and structure-activity relationship (SAR) analysis of selected inhibitors from our refined list of 320 compounds, we demonstrated that three inhibitors with 50% inhibitory concentrations (IC50s) of approximately 14 µM, which belonged to a distinct chemical cluster, were able to penetrate the Gram-negative cell membrane and prevent formation of flagella.

Exhaustive docking and solvated interaction energy scoring: lessons learned from the SAMPL4 challenge.

We continued prospective assessments of the Wilma-solvated interaction energy (SIE) platform for pose prediction, binding affinity prediction, and virtual screening on the challenging SAMPL4 data sets including the HIV-integrase inhibitor and two host-guest systems. New features of the docking algorithm and scoring function are tested here prospectively for the first time. Wilma-SIE provides good correlations with actual binding affinities over a wide range of binding affinities that includes strong binders as in the case of SAMPL4 host-guest systems. Absolute binding affinities are also reproduced with appropriate training of the scoring function on available data sets or from comparative estimation of the change in target's vibrational entropy. Even when binding modes are known, SIE predictions lack correlation with experimental affinities within dynamic ranges below 2 kcal/mol as in the case of HIV-integrase ligands, but they correctly signaled the narrowness of the dynamic range. Using a common protein structure for all ligands can reduce the noise, while incorporating a more sophisticated solvation treatment improves absolute predictions. The HIV-integrase virtual screening data set consists of promiscuous weak binders with relatively high flexibility and thus it falls outside of the applicability domain of the Wilma-SIE docking platform. Despite these difficulties, unbiased docking around three known binding sites of the enzyme resulted in over a third of ligands being docked within 2 Å from their actual poses and over half of the ligands docked in the correct site, leading to better-than-random virtual screening results.

Optimizing Antibody-Antigen Binding Affinities with the ADAPT Platform.

The ADAPT (Assisted Design of Antibody and Protein Therapeutics) platform guides the selection of mutants that improve/modulate the affinity of antibodies and other biologics. Predicted affinities are based on a consensus z-score from three scoring functions. Computational predictions are interleaved with experimental validation, significantly enhancing the robustness of the design and selection of mutants. A key step is an initial exhaustive virtual single-mutant scan that identifies hot spots and the mutations predicted to improve affinity. A small number of proposed single mutants are then produced and assayed. Only the validated single mutants (i.e., having improved affinity) are used to design double and higher-order mutants in subsequent rounds of design, avoiding the combinatorial explosion that arises from random mutagenesis. Typically, with a total of about 30-50 designed single, double, and triple mutants, affinity improvements of 10- to 100-fold are obtained.

Solvated interaction energy: from small-molecule to antibody drug design.

Scoring functions are ubiquitous in structure-based drug design as an aid to predicting binding modes and estimating binding affinities. Ideally, a scoring function should be broadly applicable, obviating the need to recalibrate and refit its parameters for every new target and class of ligands. Traditionally, drugs have been small molecules, but in recent years biologics, particularly antibodies, have become an increasingly important if not dominant class of therapeutics. This makes the goal of having a transferable scoring function, i.e., one that spans the range of small-molecule to protein ligands, even more challenging. One such broadly applicable scoring function is the Solvated Interaction Energy (SIE), which has been developed and applied in our lab for the last 15 years, leading to several important applications. This physics-based method arose from efforts to understand the physics governing binding events, with particular care given to the role played by solvation. SIE has been used by us and many independent labs worldwide for virtual screening and discovery of novel small-molecule binders or optimization of known drugs. Moreover, without any retraining, it is found to be transferrable to predictions of antibody-antigen relative binding affinities and as accurate as functions trained on protein-protein binding affinities. SIE has been incorporated in conjunction with other scoring functions into ADAPT (Assisted Design of Antibody and Protein Therapeutics), our platform for affinity modulation of antibodies. Application of ADAPT resulted in the optimization of several antibodies with 10-to-100-fold improvements in binding affinity. Further applications included broadening the specificity of a single-domain antibody to be cross-reactive with virus variants of both SARS-CoV-1 and SARS-CoV-2, and the design of safer antibodies by engineering of a pH switch to make them more selective towards acidic tumors while sparing normal tissues at physiological pH.

Exploring rigid-backbone protein docking in biologics discovery: a test using the DARPin scaffold.

Accurate protein-protein docking remains challenging, especially for artificial biologics not coevolved naturally against their protein targets, like antibodies and other engineered scaffolds. We previously developed ProPOSE, an exhaustive docker with full atomistic details, which delivers cutting-edge performance by allowing side-chain rearrangements upon docking. However, extensive protein backbone flexibility limits its practical applicability as indicated by unbound docking tests. To explore the usefulness of ProPOSE on systems with limited backbone flexibility, here we tested the engineered scaffold DARPin, which is characterized by its relatively rigid protein backbone. A prospective screening campaign was undertaken, in which sequence-diversified DARPins were docked and ranked against a directed epitope on the target protein BCL-W. In this proof-of-concept study, only a relatively small set of 2,213 diverse DARPin interfaces were selected for docking from the huge theoretical library from mutating 18 amino-acid positions. A computational selection protocol was then applied for enrichment of binders based on normalized computed binding scores and frequency of binding modes against the predefined epitope. The top-ranked 18 designed DARPin interfaces were selected for experimental validation. Three designs exhibited binding affinities to BCL-W in the nanomolar range comparable to control interfaces adopted from known DARPin binders. This result is encouraging for future screening and engineering campaigns of DARPins and possibly other similarly rigid scaffolds against targeted protein epitopes. Method limitations are discussed and directions for future refinements are proposed.

Naphthalene-based RNA editing inhibitor blocks RNA editing activities and editosome assembly in Trypanosoma brucei.

RNA editing, catalyzed by the multiprotein editosome complex, is an essential step for the expression of most mitochondrial genes in trypanosomatid pathogens. It has been shown previously that Trypanosoma brucei RNA editing ligase 1 (TbREL1), a core catalytic component of the editosome, is essential in the mammalian life stage of these parasitic pathogens. Because of the availability of its crystal structure and absence from human, the adenylylation domain of TbREL1 has recently become the focus of several studies for designing inhibitors that target its adenylylation pocket. Here, we have studied new and existing inhibitors of TbREL1 to better understand their mechanism of action. We found that these compounds are moderate to weak inhibitors of adenylylation of TbREL1 and in fact enhance adenylylation at higher concentrations of protein. Nevertheless, they can efficiently block deadenylylation of TbREL1 in the editosome and, consequently, result in inhibition of the ligation step of RNA editing. Further experiments directly showed that the studied compounds inhibit the interaction of the editosome with substrate RNA. This was supported by the observation that not only the ligation activity of TbREL1 but also the activities of other editosome proteins such as endoribonuclease, terminal RNA uridylyltransferase, and uridylate-specific exoribonuclease, all of which require the interaction of the editosome with the substrate RNA, are efficiently inhibited by these compounds. In addition, we found that these compounds can interfere with the integrity and/or assembly of the editosome complex, opening the exciting possibility of using them to study the mechanism of assembly of the editosome components.

Predicting hydration free energies of polychlorinated aromatic compounds from the SAMPL-3 data set with FiSH and LIE models.

Next-generation solvation models are devised to mimic the accuracy and generality of explicit solvation models at the speed of current popular implicit solvation models. One such method is the first-shell of hydration (FiSH) continuum model that was trained on hydration energetics from LIE calculations and molecular dynamics simulations in explicit solvent. Here we tested prospectively the FiSH model on the SAMPL-3 hydration data set that zooms in the effect of chlorination on solvation. We compare these FiSH predictions with those from retrospective LIE calculations. We find that neither FiSH nor LIE can reproduce well the absolute values and the trend of hydration free energies in the biphenyl and dioxin aromatic chlorination series. Some of the hypotheses behind this performance are discussed and tested. The LIE explicit-solvent model shows some improvement relative to the FiSH continuum model, and we correct a systematic deviation in the continuum van der Waals term of FiSH associated with aromatic Cl atom type.

Exhaustive search and solvated interaction energy (SIE) for virtual screening and affinity prediction.

We carried out a prospective evaluation of the utility of the SIE (solvation interaction energy) scoring function for virtual screening and binding affinity prediction. Since experimental structures of the complexes were not provided, this was an exercise in virtual docking as well. We used our exhaustive docking program, Wilma, to provide high-quality poses that were rescored using SIE to provide binding affinity predictions. We also tested the combination of SIE with our latest solvation model, first shell of hydration (FiSH), which captures some of the discrete properties of water within a continuum model. We achieved good enrichment in virtual screening of fragments against trypsin, with an area under the curve of about 0.7 for the receiver operating characteristic curve. Moreover, the early enrichment performance was quite good with 50% of true actives recovered with a 15% false positive rate in a prospective calculation and with a 3% false positive rate in a retrospective application of SIE with FiSH. Binding affinity predictions for both trypsin and host-guest complexes were generally within 2 kcal/mol of the experimental values. However, the rank ordering of affinities differing by 2 kcal/mol or less was not well predicted. On the other hand, it was encouraging that the incorporation of a more sophisticated solvation model into SIE resulted in better discrimination of true binders from binders. This suggests that the inclusion of proper Physics in our models is a fruitful strategy for improving the reliability of our binding affinity predictions.

Coevolved Canonical Loops Conformations of Single-Domain Antibodies: A Tale of Three Pockets Playing Musical Chairs.

Single-domain antibodies (sdAbs) are a promising class of biotherapeutics with unique structural traits within their paratope region. The distribution of canonical conformations explored by their complementarity determining region (CDR) loops differs to some extent from conventional two-chain Fv fragments of monoclonal antibodies (mAbs). In this study, we explored in detail the canonical structures of sdAb CDR-H1 and CDR-H2 loops and compared those with mAbs from the IGHV3 and IGHV1 gene families. We surveyed the antibody structures catalogued in SAbDab and clustered the CDR canonical loops in Cartesian space. While most of the sdAb clusters were sub-populations of previously defined canonical Fv conformations of CDR-H1 and CDR-H2, our stricter clustering approach defined narrower clusters in sequence-space. Meticulous visual inspection of sub-populations allowed a clearer understanding of sequence-structure relationships. The packing densities within structural pockets contacted by CDR-H1 and CDR-H2 canonical conformations were analyzed on the premise that these pockets cannot be left vacant as they would leave exposed supportive hydrophobic residues. The fine resolution of the canonical clusters defined here revealed unique signatures within these pockets, including distinct structural complementarities between CDR-H1 and CDR-H2 canonical clusters, which could not be perceived with the previous coarser clusters. We highlight examples where a single residue change in CDR-H1 sequence is sufficient to induce a dramatic population shift in CDR-H2 conformation. This suggests that preferences in combining CDR-H1 and CDR-H2 emerged naturally during antibody evolution, leading to preferred sets of conserved amino acids at key positions in the framework as well as within the CDR loops. We outline a game of musical chairs that is necessary to maintain the integrity of the antibody structures that arose during evolution. Our study also provides refined CDR-H1 and CDR-H2 structural templates for sdAb homology modeling that could be leveraged for improved antibody design.

Contribution of active site residues to substrate hydrolysis by USP2: insights into catalysis by ubiquitin specific proteases.

The ubiquitin-specific protease (USP) structural class represents the largest and most diverse family of deubiquitinating enzymes (DUBs). Many USPs assume important biological roles and emerge as potential targets for therapeutic intervention. A clear understanding of USP catalytic mechanism requires a functional evaluation of the proposed key active site residues. Crystallographic data of ubiquitin aldehyde adducts of USP catalytic cores provided structural details on the catalytic triad residues, namely the conserved Cys and His, and a variable putative third residue, and inferred indirect structural roles for two other conserved residues (Asn and Asp), in stabilizing via a bridging water molecule the oxyanion of the tetrahedral intermediate (TI). We have expressed the catalytic domain of USP2 and probed by site-directed mutagenesis the role of these active site residues in the hydrolysis of peptide and isopeptide substrates, including a synthetic K48-linked diubiquitin substrate for which a label-free, mass spectrometry based assay has been developed to monitor cleavage. Hydrolysis of ubiquitin-AMC, a model substrate, was not affected by the mutations. Molecular dynamics simulations of USP2, free and complexed with the TI of a bona fide isopeptide substrate, were carried out. We found that Asn271 is structurally poised to directly stabilize the oxyanion developed in the acylation step, while being structurally supported by the adjacent absolutely conserved Asp575. Mutagenesis data functionally confirmed this structural role independent of the nature (isopeptide vs peptide) of the bond being cleaved. We also found that Asn574, structurally located as the third member of the catalytic triad, does not fulfill this role functionally. A dual supporting role is inferred from double-point mutation and structural data for the absolutely conserved residue Asp575, in oxyanion hole formation, and in maintaining the correct alignment and protonation of His557 for catalytic competency.

A monovalent agonist of TrkA tyrosine kinase receptors can be converted into a bivalent antagonist.

BACKGROUND: Receptor tyrosine kinases (RTK) act through dimerization. Previously it was thought that only bivalent ligands could be agonistic, whereas monovalent ligands should be antagonistic. This notion changed after the demonstration that monovalent ligands can be agonistic, including our report of a small molecule monovalent ligand "D3" that is a partial agonist of the NGF receptor TrkA. A bivalent "D3-linker-D3" was expected to increase agonism. METHODS: Dimeric analogs were synthesized and tested in binding, biochemical, and biological assays. RESULTS: One analog, 1-ss, binds TrkA with higher affinity than D3 and induces or stabilizes receptor dimers. However, 1-ss exhibited antagonistic activity, through two mechanisms. One mechanism is that 1-ss blocks NGF binding, unlike D3 which is non-competitive. Inhibition of NGF binding may be due to the linker of 1-ss filling the inter-receptor space that NGF traverses before docking. In a second mechanism, 1-ss acts as a pure antagonist, inhibiting NGF-independent TrkA activity in cells over-expressing receptors. Inhibition is likely due to 1-ss "freezing" the TrkA dimer in the inactive state. CONCLUSIONS: Dimerization of an RTK can result in antagonism, through two independent mechanisms. GENERAL SIGNIFICANCE: we report a small molecule monovalent agonist being converted to a bivalent antagonist.

Molecular dynamics study of small molecule inhibitors of the Bcl-2 family.

We carried out docking and molecular dynamics simulations on ABT-737 and obatoclax, which are inhibitors of the Bcl-2 family of proteins. We modeled the binding mode of ABT-737 with Bcl-x(L) , Bcl-2, and Mcl-1 and examined their dynamical behavior. We found that the binding of the chlorobiphenyl end of ABT-737 was quite stable across all three proteins. However, the phenylpiperazine linker group was dramatically more mobile in Mcl-1 compared to either Bcl-x(L) or Bcl-2. The S-phenyl group at the p4 binding site was well-anchored in Bcl-x(L) and Bcl-2 but was somewhat more mobile in Mcl-1 although the phenyl ring itself on average stayed close to the p4 binding site in Mcl-1. This greater mobility is likely due to the greater openness of the p3 and p4 binding sites on Mcl-1. The calculated binding free energies were consistent with the much weaker binding affinity of ABT-737 for Mcl-1. Obatoclax was predicted to bind at the p1 and p2 binding sites of Mcl-1 and the binding mode was quite stable during the molecular dynamics simulation with Mcl-1 wrapping around the molecule. The modeled binding mode suggests that obatoclax is able to inhibit all three proteins because it makes use of the p1 and p2 binding sites alone, which is a fairly narrow groove in all three proteins unlike the p4 binding site, which is much broader in Mcl-1.

Solvated interaction energy (SIE) for scoring protein-ligand binding affinities. 2. Benchmark in the CSAR-2010 scoring exercise.

Solvated interaction energy (SIE) is an end-point physics-based scoring function for predicting binding affinities from force-field nonbonded interaction terms, continuum solvation, and configurational entropy linear compensation. We tested the SIE function in the Community Structure-Activity Resource (CSAR) scoring challenge consisting of high-resolution cocrystal structures for 343 protein-ligand complexes with high-quality binding affinity data and high diversity with respect to protein targets. Particular emphasis was placed on the sensitivity of SIE predictions to the assignment of protonation and tautomeric states in the complex and the treatment of metal ions near the protein-ligand interface. These were manually curated from an originally distributed CSAR-HiQ data set version, leading to the currently distributed CSAR-NRC-HiQ version. We found that this manual curation was a critical step for accurately testing the performance of the SIE function. The standard SIE parametrization, previously calibrated on an independent data set, predicted absolute binding affinities with a mean-unsigned-error (MUE) of 2.41 kcal/mol for the CSAR-HiQ version, which improved to 1.98 kcal/mol for the upgraded CSAR-NRC-HiQ version. Half-half retraining-testing of SIE parameters on two predefined subsets of CSAR-NRC-HiQ led to only marginal further improvements to an MUE of 1.83 kcal/mol. Hence, we do not recommend altering the current default parameters of SIE at this time. For a sample of SIE outliers, additional calculations by molecular dynamics-based SIE averaging with or without incorporation of ligand strain, by MM-PB(GB)/SA methods with or without entropic estimates, or even by the linear interaction energy (LIE) formalism with an explicit solvent model, did not further improve predictions.