Hi all, I was using the residue depth module from Bio.PDB and extracting the residue depth of proteins. However, I randomly input a protein and found out that the residue depth are too similar among residues (1.5-1.9A).I tried different proteins and had similar results. I expected to have a bigger deviation and larger residue depth. Anyone has any idea on how to interpret this seemingly incorrect results.

Coding:

parser = MMCIFParser() structure = parser.get_structure('test', 'PDB/1qmo.cif') model = structure[0] chain = model['A'] surface = get_surface(model) for each in range(1,100): resi = chain[each] rd = ResidueDepth(resi, surface) resi_depth,ca_depth=rd[rd.keys()[0]] print(resi.get_resname(),each,"resi_depth:",resi_depth,"ca_depth:",ca_depth)

Output:

ALA 1 resi_depth: 1.76746537894

GLN 2 resi_depth: 1.75285448018

SER 3 resi_depth: 1.73959646157

LEU 4 resi_depth: 1.82207581001

SER 5 resi_depth: 1.73955300311

PHE 6 resi_depth: 1.8067918142

SER 7 resi_depth: 1.73951724545

PHE 8 resi_depth: 1.80683567125

THR 9 resi_depth: 1.77673089694

LYS 10 resi_depth: 1.76756483127

PHE 11 resi_depth: 1.80688191791

ASP 12 resi_depth: 1.67205727412

PRO 13 resi_depth: 1.83379116059

ASN 14 resi_depth: 1.72208197147

GLN 15 resi_depth: 1.7529624168

GLU 16 resi_depth: 1.70843598225

ASP 17 resi_depth: 1.67203387621

LEU 18 resi_depth: 1.8220660772

ILE 19 resi_depth: 1.85456052148

PHE 20 resi_depth: 1.80679806743

GLN 21 resi_depth: 1.75289893794

GLY 22 resi_depth: 1.70963404182

HIS 23 resi_depth: 1.75363235972

ALA 24 resi_depth: 1.76757734259

THR 25 resi_depth: 1.77668049

SER 26 resi_depth: 1.73960713832

THR 27 resi_depth: 1.77673852224

ASN 28 resi_depth: 1.72209344522

ASN 29 resi_depth: 1.72204425256

VAL 30 resi_depth: 1.83378782042

LEU 31 resi_depth: 1.82205552799

GLN 32 resi_depth: 1.75291631342

VAL 33 resi_depth: 1.83386014702

THR 34 resi_depth: 1.77672868555

LYS 35 resi_depth: 1.76759233854

LEU 36 resi_depth: 1.82211062771

ASP 37 resi_depth: 1.67206662754

SER 38 resi_depth: 1.73951018538

ALA 39 resi_depth: 1.76750116214

GLY 40 resi_depth: 1.70948746419

ASN 41 resi_depth: 1.72215038037

PRO 42 resi_depth: 1.8338081986

VAL 43 resi_depth: 1.83392179311

SER 44 resi_depth: 1.73966523175

SER 45 resi_depth: 1.739524853

SER 46 resi_depth: 1.73944782784

ALA 47 resi_depth: 1.76764147231

GLY 48 resi_depth: 1.70945286317

ARG 49 resi_depth: 1.80681924879

VAL 50 resi_depth: 1.83390929813

LEU 51 resi_depth: 1.82205562777

TYR 52 resi_depth: 1.77962717968

SER 53 resi_depth: 1.7395572628

ALA 54 resi_depth: 1.76755923724

PRO 55 resi_depth: 1.83388677583

LEU 56 resi_depth: 1.82205880098

ARG 57 resi_depth: 1.80685753138

LEU 58 resi_depth: 1.82203206138

TRP 59 resi_depth: 1.78952236069

GLU 60 resi_depth: 1.70846381898

ASP 61 resi_depth: 1.67212575224

SER 62 resi_depth: 1.73949591106

ALA 63 resi_depth: 1.76749955914

VAL 64 resi_depth: 1.83385779002

LEU 65 resi_depth: 1.82206430838

THR 66 resi_depth: 1.77673042203

SER 67 resi_depth: 1.73957876291

PHE 68 resi_depth: 1.80681401187

ASP 69 resi_depth: 1.67210216411

THR 70 resi_depth: 1.77667940948

ILE 71 resi_depth: 1.85456746315

ILE 72 resi_depth: 1.85452470948

ASN 73 resi_depth: 1.7220897346

PHE 74 resi_depth: 1.80684148809

GLU 75 resi_depth: 1.7084363719

ILE 76 resi_depth: 1.85454488214

SER 77 resi_depth: 1.73950168541

THR 78 resi_depth: 1.77665741506

PRO 79 resi_depth: 1.8337830683

TYR 80 resi_depth: 1.77954354275

THR 81 resi_depth: 1.77672941066

SER 82 resi_depth: 1.7394912958

ARG 83 resi_depth: 1.76752844782

ILE 84 resi_depth: 1.8545700946

ALA 85 resi_depth: 1.76750466164

ASP 86 resi_depth: 1.67206078958

GLY 87 resi_depth: 1.70953721952

LEU 88 resi_depth: 1.82205449959

ALA 89 resi_depth: 1.76757115457

PHE 90 resi_depth: 1.80682955618

PHE 91 resi_depth: 1.8068518812

ILE 92 resi_depth: 1.85456522545

ALA 93 resi_depth: 1.76751459015

PRO 94 resi_depth: 1.83381213235

PRO 95 resi_depth: 1.83391253076

ASP 96 resi_depth: 1.67205295932

SER 97 resi_depth: 1.73953674539

VAL 98 resi_depth: 1.83378935217

ILE 99 resi_depth: 1.85448345625