J Chem Inf Model - CSAR scoring challenge reveals the need for new concepts in estimating protein-ligand binding affinity.


{ bind(1733) structur(1185) ligand(1036) }
{ studi(1119) effect(1106) posit(819) }
{ take(945) account(800) differ(722) }
{ model(2341) predict(2261) use(1141) }
{ sequenc(1873) structur(1644) protein(1328) }
{ featur(3375) classif(2383) classifi(1994) }
{ chang(1828) time(1643) increas(1301) }
{ method(2212) result(1239) propos(1039) }
{ howev(809) still(633) remain(590) }
{ use(976) code(926) identifi(902) }
{ method(1219) similar(1157) match(930) }
{ patient(2837) hospit(1953) medic(668) }
{ cost(1906) reduc(1198) effect(832) }
{ error(1145) method(1030) estim(1020) }
{ risk(3053) factor(974) diseas(938) }
{ research(1085) discuss(1038) issu(1018) }
{ group(2977) signific(1463) compar(1072) }
{ can(981) present(881) function(850) }
{ method(1969) cluster(1462) data(1082) }
{ data(1737) use(1416) pattern(1282) }
{ measur(2081) correl(1212) valu(896) }
{ imag(1057) registr(996) error(939) }
{ imag(2675) segment(2577) method(1081) }
{ patient(2315) diseas(1263) diabet(1191) }
{ method(1557) propos(1049) approach(1037) }
{ data(1714) softwar(1251) tool(1186) }
{ design(1359) user(1324) use(1319) }
{ system(1050) medic(1026) inform(1018) }
{ import(1318) role(1303) understand(862) }
{ perform(1367) use(1326) method(1137) }
{ model(3480) simul(1196) paramet(876) }
{ ehr(2073) health(1662) electron(1139) }
{ intervent(3218) particip(2042) group(1664) }
{ patient(1821) servic(1111) care(1106) }
{ use(1733) differ(960) four(931) }
{ activ(1452) weight(1219) physic(1104) }
{ model(3404) distribut(989) bayesian(671) }
{ can(774) often(719) complex(702) }
{ imag(1947) propos(1133) code(1026) }
{ inform(2794) health(2639) internet(1427) }
{ system(1976) rule(880) can(841) }
{ imag(2830) propos(1344) filter(1198) }
{ network(2748) neural(1063) input(814) }
{ studi(2440) review(1878) systemat(933) }
{ motion(1329) object(1292) video(1091) }
{ assess(1506) score(1403) qualiti(1306) }
{ treatment(1704) effect(941) patient(846) }
{ surgeri(1148) surgic(1085) robot(1054) }
{ framework(1458) process(801) describ(734) }
{ problem(2511) optim(1539) algorithm(950) }
{ learn(2355) train(1041) set(1003) }
{ concept(1167) ontolog(924) domain(897) }
{ clinic(1479) use(1117) guidelin(835) }
{ algorithm(1844) comput(1787) effici(935) }
{ extract(1171) text(1153) clinic(932) }
{ control(1307) perform(991) simul(935) }
{ model(2220) cell(1177) simul(1124) }
{ care(1570) inform(1187) nurs(1089) }
{ general(901) number(790) one(736) }
{ method(984) reconstruct(947) comput(926) }
{ search(2224) databas(1162) retriev(909) }
{ featur(1941) imag(1645) propos(1176) }
{ case(1353) use(1143) diagnosi(1136) }
{ data(3963) clinic(1234) research(1004) }
{ studi(1410) differ(1259) use(1210) }
{ perform(999) metric(946) measur(919) }
{ visual(1396) interact(850) tool(830) }
{ compound(1573) activ(1297) structur(1058) }
{ blood(1257) pressur(1144) flow(957) }
{ spatial(1525) area(1432) region(1030) }
{ record(1888) medic(1808) patient(1693) }
{ health(3367) inform(1360) care(1135) }
{ monitor(1329) mobil(1314) devic(1160) }
{ state(1844) use(1261) util(961) }
{ research(1218) medic(880) student(794) }
{ model(2656) set(1616) predict(1553) }
{ data(2317) use(1299) case(1017) }
{ age(1611) year(1155) adult(843) }
{ medic(1828) order(1363) alert(1069) }
{ signal(2180) analysi(812) frequenc(800) }
{ sampl(1606) size(1419) use(1276) }
{ gene(2352) biolog(1181) express(1162) }
{ data(3008) multipl(1320) sourc(1022) }
{ first(2504) two(1366) second(1323) }
{ activ(1138) subject(705) human(624) }
{ time(1939) patient(1703) rate(768) }
{ use(2086) technolog(871) perceiv(783) }
{ analysi(2126) use(1163) compon(1037) }
{ health(1844) social(1437) communiti(874) }
{ structur(1116) can(940) graph(676) }
{ high(1669) rate(1365) level(1280) }
{ cancer(2502) breast(956) screen(824) }
{ drug(1928) target(777) effect(648) }
{ result(1111) use(1088) new(759) }
{ implement(1333) system(1263) develop(1122) }
{ survey(1388) particip(1329) question(1065) }
{ estim(2440) model(1874) function(577) }
{ decis(3086) make(1611) patient(1517) }
{ process(1125) use(805) approach(778) }
{ detect(2391) sensit(1101) algorithm(908) }


The dG prediction accuracy by the Lead Finder docking software on the CSAR test set was characterized by R(2)=0.62 and rmsd=1.93 kcal/mol, and the method of preparation of the full-atom structures of the test set did not significantly affect the resulting accuracy of predictions. The primary factors determining the correlation between the predicted and experimental values were the van der Waals interactions and solvation effects. Those two factors alone accounted for R(2)=0.50. The other factors that affected the accuracy of predictions, listed in the order of decreasing importance, were the change of ligand's internal energy upon binding with protein, the electrostatic interactions, and the hydrogen bonds. It appears that those latter factors contributed to the independence of the prediction results from the method of full-atom structure preparation. Then, we turned our attention to the other factors that could potentially improve the scoring function in order to raise the accuracy of the dG prediction. It turned out that the ligand-centric factors, including Mw, cLogP, PSA, etc. or protein-centric factors, such as the functional class of protein, did not improve the prediction accuracy. Following that, we explored if the weak molecular interactions such as X-H...Ar, X-H...Hal, CO...Hal, C-H...X, stacking and p-cationic interactions (where X is N or O), that are generally of interest to the medicinal chemists despite their lack of proper molecular mechanical parametrization, could improve dG prediction. Our analysis revealed that out of these new interactions only CO...Hal is statistically significant for dG predictions using Lead FInder scoring function. Accounting for the CO...Hal interaction resulted in the reduction of the rmsd from 2.19 to 0.69 kcal/mol for the corresponding structures. The other weak interaction factors were not statistically significant and therefore irrelevant to the accuracy of dG prediction. On the basis of our findings from our participation in the CSAR scoring challenge we conclude that a significant increase of accuracy predictions necessitates breakthrough scoring approaches. We anticipate that the explicit accounting for water molecules, protein flexibility, and a more thermodynamically accurate method of dG calculation rather than single point energy calculation may lead to such breakthroughs.

Resumo Limpo

dg predict accuraci lead finder dock softwar csar test set character r rmsd kcalmol method prepar fullatom structur test set signific affect result accuraci predict primari factor determin correl predict experiment valu van der waal interact solvat effect two factor alon account r factor affect accuraci predict list order decreas import chang ligand intern energi upon bind protein electrostat interact hydrogen bond appear latter factor contribut independ predict result method fullatom structur prepar turn attent factor potenti improv score function order rais accuraci dg predict turn ligandcentr factor includ mw clogp psa etc proteincentr factor function class protein improv predict accuraci follow explor weak molecular interact xhar xhhal cohal chx stack pcation interact x n o general interest medicin chemist despit lack proper molecular mechan parametr improv dg predict analysi reveal new interact cohal statist signific dg predict use lead finder score function account cohal interact result reduct rmsd kcalmol correspond structur weak interact factor statist signific therefor irrelev accuraci dg predict basi find particip csar score challeng conclud signific increas accuraci predict necessit breakthrough score approach anticip explicit account water molecul protein flexibl thermodynam accur method dg calcul rather singl point energi calcul may lead breakthrough

Resumos Similares

J Chem Inf Model - In silico mutagenesis and docking study of Ralstonia solanacearum RSL lectin: performance of docking software to predict saccharide binding. ( 0,793325387421782 )
J Chem Inf Model - Analysis of factors influencing hydration site prediction based on molecular dynamics simulations. ( 0,780698353735051 )
J Chem Inf Model - Improving docking results via reranking of ensembles of ligand poses in multiple X-ray protein conformations with MM-GBSA. ( 0,7691522160399 )
J Chem Inf Model - Hydration properties of ligands and drugs in protein binding sites: tightly-bound, bridging water molecules and their effects and consequences on molecular design strategies. ( 0,764224760486548 )
J Chem Inf Model - Structure-based multiscale approach for identification of interaction partners of PDZ domains. ( 0,762157283891939 )
J Chem Inf Model - The molecular basis for the selectivity of tadalafil toward phosphodiesterase 5 and 6: a modeling study. ( 0,760782354688735 )
Comput Biol Chem - Computational simulation of ligand docking to L-type pyruvate kinase subunit. ( 0,760706694904356 )
J Chem Inf Model - Dynamics of noncovalent interactions in all-a and all-? class proteins: implications for the stability of amyloid aggregates. ( 0,760152409598031 )
J Chem Inf Model - Predicted structures and dynamics for agonists and antagonists bound to serotonin 5-HT2B and 5-HT2C receptors. ( 0,759135884687891 )
J Chem Inf Model - Correlation analyses on binding affinity of sialic acid analogues and anti-influenza drugs with human neuraminidase using ab initio MO calculations on their complex structures--LERE-QSAR analysis (IV). ( 0,753499801524682 )
J Chem Inf Model - Including explicit water molecules as part of the protein structure in MM/PBSA calculations. ( 0,753286508423549 )
J Chem Inf Model - Modeling anesthetic binding sites within the glycine alpha one receptor based on prokaryotic ion channel templates: the problem with TM4. ( 0,750624598612215 )
J Chem Inf Model - Application of binding free energy calculations to prediction of binding modes and affinities of MDM2 and MDMX inhibitors. ( 0,748358285588865 )
J Chem Inf Model - Thermodynamics of fragment binding. ( 0,746645848494412 )
Comput Biol Chem - Molecular dynamics studies of ?-hairpin folding with the presence of the sodium ion. ( 0,746644835265505 )
J Chem Inf Model - Interference of boswellic acids with the ligand binding domain of the glucocorticoid receptor. ( 0,746556747307147 )
Comput Biol Chem - A computational prospect to aspirin side effects: aspirin and COX-1 interaction analysis based on non-synonymous SNPs. ( 0,744311814581251 )
J Chem Inf Model - Strategies for improved modeling of GPCR-drug complexes: blind predictions of serotonin receptors bound to ergotamine. ( 0,742947130004075 )
J Chem Inf Model - Approximating protein flexibility through dynamic pharmacophore models: application to fatty acid amide hydrolase (FAAH). ( 0,742635690772021 )
J Chem Inf Model - Automated docking with protein flexibility in the design of femtomolar click chemistry inhibitors of acetylcholinesterase. ( 0,742534620865962 )
Comput. Biol. Med. - Theoretical study of 3-D molecular similarity and ligand binding modes of orthologous human and rat D2 dopamine receptors. ( 0,740560613791581 )
Comput Biol Chem - Protein function prediction using neighbor relativity in protein-protein interaction network. ( 0,739639910090428 )
J Chem Inf Model - Unraveling the allosteric inhibition mechanism of PTP1B by free energy calculation based on umbrella sampling. ( 0,73939493578207 )
J Chem Inf Model - Exploring the role of water molecules for docking and receptor guided 3D-QSAR analysis of naphthyridine derivatives as spleen tyrosine kinase (Syk) inhibitors. ( 0,738332045100852 )
J Chem Inf Model - Dependences of water permeation through cyclic octa-peptide nanotubes on channel length and membrane thickness. ( 0,738080557163048 )
J Chem Inf Model - Structural and energetic analysis of 2-aminobenzimidazole inhibitors in complex with the hepatitis C virus IRES RNA using molecular dynamics simulations. ( 0,737483201977297 )
J Chem Inf Model - Matching cavities in g protein-coupled receptors to infer ligand-binding sites. ( 0,737354744767919 )
J Chem Inf Model - Comparative study on the use of docking and Bayesian categorization to predict ligand binding to nicotinic acetylcholine receptors (nAChRs) subtypes. ( 0,734968221877444 )
J Chem Inf Model - Snooker: a structure-based pharmacophore generation tool applied to class A GPCRs. ( 0,734283888712138 )
J Chem Inf Model - Key binding and susceptibility of NS3/4A serine protease inhibitors against hepatitis C virus. ( 0,734232281421061 )
J Chem Inf Model - Significant enhancement of docking sensitivity using implicit ligand sampling. ( 0,733128692316949 )
J Chem Inf Model - Impact of resistance mutations on inhibitor binding to HIV-1 integrase. ( 0,731729164949241 )
J Chem Inf Model - Binding selectivity studies of phosphoinositide 3-kinases using free energy calculations. ( 0,730747748198065 )
J Chem Inf Model - Insights into AT1 receptor activation through AngII binding studies. ( 0,730506575573172 )
J Chem Inf Model - Halogen interactions in protein-ligand complexes: implications of halogen bonding for rational drug design. ( 0,730355922438877 )
J Chem Inf Model - Computational insight into small molecule inhibition of cyclophilins. ( 0,728509163846838 )
J Chem Inf Model - Understanding the impact of the P-loop conformation on kinase selectivity. ( 0,727909670626613 )
J Chem Inf Model - Structural basis of specific binding between Aurora A and TPX2 by molecular dynamics simulations. ( 0,727501423006227 )
J Chem Inf Model - Profiling the structural determinants for the selectivity of representative factor-Xa and thrombin inhibitors using combined ligand-based and structure-based approaches. ( 0,727134283994304 )
J Chem Inf Model - Molecular dynamics simulations of CXCL-8 and its interactions with a receptor peptide, heparin fragments, and sulfated linked cyclitols. ( 0,726910918935433 )
Comput Biol Chem - Fine grained sampling of residue characteristics using molecular dynamics simulation. ( 0,726744817363102 )
J Chem Inf Model - 3D structure prediction of TAS2R38 bitter receptors bound to agonists phenylthiocarbamide (PTC) and 6-n-propylthiouracil (PROP). ( 0,726563875557985 )
J Chem Inf Model - The large scale conformational change of the human DPP III-substrate prefers the closed form. ( 0,726551012243847 )
J Chem Inf Model - Cytochrome P450 3A4 inhibition by ketoconazole: tackling the problem of ligand cooperativity using molecular dynamics simulations and free-energy calculations. ( 0,72611189341443 )
J Chem Inf Model - X-ray crystallographic structures as a source of ligand alignment in 3D-QSAR. ( 0,725807401388089 )
J Chem Inf Model - Structurally conserved binding sites of hemagglutinin as targets for influenza drug and vaccine development. ( 0,725609224902564 )
J Chem Inf Model - Computational rationale for the selective inhibition of the herpes simplex virus type 1 uracil-DNA glycosylase enzyme. ( 0,725396927099059 )
J Chem Inf Model - Ligand aligning method for molecular docking: alignment of property-weighted vectors. ( 0,724732853061461 )
J Chem Inf Model - Computational modeling of the catalytic mechanism of human placental alkaline phosphatase (PLAP). ( 0,724587612935938 )
J Chem Inf Model - Correlating protein hot spot surface analysis using ProBiS with simulated free energies of protein-protein interfacial residues. ( 0,723956658827237 )
J Chem Inf Model - Multiple interaction regions in the orthosteric ligand binding domain of the a7 neuronal nicotinic acetylcholine receptor. ( 0,723682206572228 )
J Chem Inf Model - Investigation on the effect of key water molecules on docking performance in CSARdock exercise. ( 0,723671209253344 )
J Chem Inf Model - Ligand Identification Scoring Algorithm (LISA). ( 0,722603033489578 )
J Chem Inf Model - Ligand-induced structural changes in TEM-1 probed by molecular dynamics and relative binding free energy calculations. ( 0,722327497911701 )
J Chem Inf Model - Docking challenge: protein sampling and molecular docking performance. ( 0,720718383856378 )
J Chem Inf Model - Automated large-scale file preparation, docking, and scoring: evaluation of ITScore and STScore using the 2012 Community Structure-Activity Resource benchmark. ( 0,720018593809192 )
J Chem Inf Model - A contribution to the drug resistance mechanism of darunavir, amprenavir, indinavir, and saquinavir complexes with HIV-1 protease due to flap mutation I50V: a systematic MM-PBSA and thermodynamic integration study. ( 0,720005981010166 )
J Chem Inf Model - Numerical errors in minimization based binding energy calculations. ( 0,719448195522404 )
J Chem Inf Model - Calculation of the solvation free energy of neutral and ionic molecules in diverse solvents. ( 0,719329954710504 )
J Chem Inf Model - Theoretical studies on the interactions and interferences of HIV-1 glycoprotein gp120 and its coreceptor CCR5. ( 0,718887158858217 )
J Chem Inf Model - Insights into the conformational switching mechanism of the human vascular endothelial growth factor receptor type 2 kinase domain. ( 0,718228179805134 )
J Chem Inf Model - Application of the docking program SOL for CSAR benchmark. ( 0,717367215467759 )
J Chem Inf Model - Elucidation of allosteric inhibition mechanism of 2-Cys human peroxiredoxin by molecular modeling. ( 0,714865053936494 )
J Chem Inf Model - Molecular docking with ligand attached water molecules. ( 0,7147725063783 )
J Chem Inf Model - Structural insights into the molecular basis of the ligand promiscuity. ( 0,713956768057786 )
J Chem Inf Model - Strategies to calculate water binding free energies in protein-ligand complexes. ( 0,713159578384308 )
J Chem Inf Model - MMGBSA as a tool to understand the binding affinities of filamin-peptide interactions. ( 0,713148367607102 )
J Chem Inf Model - Molecular dynamics simulation and free energy calculation studies of the binding mechanism of allosteric inhibitors with p38a MAP kinase. ( 0,712150931497924 )
J Chem Inf Model - Conformational analysis of 6a- and 6?-naltrexol and derivatives and relationship to opioid receptor affinity. ( 0,711781224525316 )
J Chem Inf Model - Solvent interaction energy calculations on molecular dynamics trajectories: increasing the efficiency using systematic frame selection. ( 0,711645166007419 )
J Chem Inf Model - Influence of protonation on substrate and inhibitor interactions at the active site of human monoamine oxidase-A. ( 0,711517922267325 )
J Chem Inf Model - Evaluation of several two-step scoring functions based on linear interaction energy, effective ligand size, and empirical pair potentials for prediction of protein-ligand binding geometry and free energy. ( 0,711260810846678 )
J Chem Inf Model - HADDOCK(2P2I): a biophysical model for predicting the binding affinity of protein-protein interaction inhibitors. ( 0,7112153828091 )
J Chem Inf Model - Ligand-receptor affinities computed by an adapted linear interaction model for continuum electrostatics and by protein conformational averaging. ( 0,711204021724678 )
J Chem Inf Model - Computational analysis of human OGA structure in complex with PUGNAc and NAG-thiazoline derivatives. ( 0,710294295621948 )
J Chem Inf Model - Comparative binding effects of aspirin and anti-inflammatory Cu complex in the active site of LOX-1. ( 0,70978641338543 )
J Chem Inf Model - Analyzing the topology of active sites: on the prediction of pockets and subpockets. ( 0,70931369510896 )
J Chem Inf Model - Statistical potential for modeling and ranking of protein-ligand interactions. ( 0,70924558938034 )
J Chem Inf Model - Elements of nucleotide specificity in the Trypanosoma brucei mitochondrial RNA editing enzyme RET2. ( 0,708138531298818 )
Comput Biol Chem - Docking assay of small molecule antivirals to p7 of HCV. ( 0,707769021880737 )
J Chem Inf Model - Insight into the fundamental interactions between LEDGF binding site inhibitors and integrase combining docking and molecular dynamics simulations. ( 0,707739697590465 )
J Chem Inf Model - Flexibility and explicit solvent in molecular-dynamics-based docking of protein-glycosaminoglycan systems. ( 0,707736688842417 )
J Chem Inf Model - A negative cooperativity mechanism of human CYP2E1 inferred from molecular dynamics simulations and free energy calculations. ( 0,707254252801935 )
J Chem Inf Model - Assessing hERG pore models as templates for drug docking using published experimental constraints: the inactivated state in the context of drug block. ( 0,707119332099499 )
J Chem Inf Model - Current assessment of docking into GPCR crystal structures and homology models: successes, challenges, and guidelines. ( 0,706942724389876 )
J Chem Inf Model - GalaxyDock: protein-ligand docking with flexible protein side-chains. ( 0,706900797482523 )
J Chem Inf Model - Comprehensive classification and diversity assessment of atomic contacts in protein-small ligand interactions. ( 0,706732375784413 )
J. Comput. Biol. - HarmonyDOCK: the structural analysis of poses in protein-ligand docking. ( 0,706626676922326 )
J Chem Inf Model - Molecular dynamics simulation, free energy calculation and structure-based 3D-QSAR studies of B-RAF kinase inhibitors. ( 0,706585883184193 )
Comput. Biol. Med. - Cyclin-dependent kinases 5 template: useful for virtual screening. ( 0,706239306897339 )
Comput Biol Chem - Computer modeling of the dynamic properties of the cAMP-dependent protein kinase catalytic subunit. ( 0,705833403700223 )
J Chem Inf Model - AADS--an automated active site identification, docking, and scoring protocol for protein targets based on physicochemical descriptors. ( 0,705620424799539 )
J Chem Inf Model - Combining solvent thermodynamic profiles with functionality maps of the Hsp90 binding site to predict the displacement of water molecules. ( 0,704982904143312 )
J Chem Inf Model - Molecular recognition in a diverse set of protein-ligand interactions studied with molecular dynamics simulations and end-point free energy calculations. ( 0,704897511581172 )
J Chem Inf Model - Conformational free energy modeling of druglike molecules by metadynamics in the WHIM space. ( 0,704810493452797 )
J Chem Inf Model - Molecular modeling of p38a mitogen-activated protein kinase inhibitors through 3D-QSAR and molecular dynamics simulations. ( 0,704752593301396 )
J Chem Inf Model - Toward an optimal docking and free energy calculation scheme in ligand design with application to COX-1 inhibitors. ( 0,703785029320786 )
J. Comput. Biol. - A new role for the nonpathogenic nonsynonymous single-nucleotide polymorphisms of acetylcholinesterase in the treatment of Alzheimer's disease: a computational study. ( 0,703564693636074 )
J Chem Inf Model - DOLINA--docking based on a local induced-fit algorithm: application toward small-molecule binding to nuclear receptors. ( 0,703492287772224 )
J Chem Inf Model - Hands-off linear interaction energy approach to binding mode and affinity estimation of estrogens. ( 0,703167202154057 )